import json
import math
import time
import copy
import random
import numpy as np
import torch
import torch.nn as nn
import torch.optim as optim
from wsbignn import WSBiGNN
import matplotlib.pyplot as plt
from matplotlib import pyplot as plt
torch.autograd.set_detect_anomaly(True)
<torch.autograd.anomaly_mode.set_detect_anomaly at 0x7f4188763a00>
#1. set parameters
#2. visualization
#3. compute the loss
#4. initialize user embeddings
#5. compute adjacency matrix based on mobility and web search
#6. train
#7. compute the Recall and NDCG
#8. main
#9. save
print (torch.cuda.is_available())
device = torch.device("cuda:0")
random_seed = 42
random.seed(random_seed)
torch.manual_seed(random_seed)
torch.cuda.manual_seed(random_seed)
r = random.random
True
x_day, y_day = 3, 1
case = str(x_day) + "_" + str(y_day)
train_ratio, validate_ratio = 0.70, 0.10
top_k, npr = 3, 5
num_epochs, batch_size, learning_rate = 200, 2, 0.001
hid_dim = 32
hid_dim_cons = 32
hyper_param = {"n_e": num_epochs, "b_s": batch_size, "l_r": learning_rate, "top_k": top_k}
root_path = "/home/umni2/a/umnilab/users/xue120/umni4/2023_web_mobility_summer"+\
"/1_data_check/data_feature_generation/"
file_name = root_path + "feature_" + str(x_day) + "_" + str(y_day)
train_path = file_name + "/train.json"
vali_path = file_name + "/validate.json"
test_path = file_name + "/test.json"
sampled_user_location_path = file_name + "/sampled_user_location.json"
member_path = root_path + "member/"
def visual_train_loss(e_losses):
plt.figure(figsize=(4,3), dpi=300)
x = range(len(e_losses))
y1 = copy.copy(e_losses)
plt.plot(x,y1, linewidth=1, label="train")
plt.legend()
plt.title('Loss decline on training data')
plt.xlabel('Epoch')
plt.ylabel('Loss')
plt.savefig(case + '/' + 'train_loss.png',bbox_inches = 'tight')
plt.show()
def visual_vali_test_loss(recall_vali, recall_test, ndcg_vali, ndcg_test):
plt.figure(figsize=(4,3), dpi=300)
x = range(len(recall_vali))
plt.plot(x, recall_vali, linewidth=1, label="Recall_validate")
plt.plot(x, ndcg_vali, linewidth=1, label="NDCG_validate")
plt.plot(x, recall_test, linewidth=1, label="Recall_test")
plt.plot(x, ndcg_test, linewidth=1, label="NDCG_test")
plt.legend()
plt.title('Recall/NDCG on validate/test sets')
plt.xlabel('Epoch')
plt.ylabel('Recall@3, NDCG@3')
plt.savefig(case + '/' + 'vali_test_recall_ndcg.png',bbox_inches = 'tight')
plt.show()
#compute the cross entropy loss
#input1: gnn_output dim = (batch, y_day, U, V).
#input2: real_link dim = (batch, y_day, n_edge, 2).
#input3: criterion
#inputs 4,5,6: n_user, n_loc, npr
#output: average loss for batch*y_day terms
def compute_loss(gnn_output, real_link, criterion, n_user, n_loc, npr):
batch, y_day = gnn_output.size()[0], gnn_output.size()[1]
loss = torch.tensor([0.0])
all_edge = [str(u)+"_"+str(v) for u in range(n_user) for v in range(n_loc)]
for i in range(batch):
for j in range(y_day):
predicted, real = gnn_output[i][j], real_link[i][j]
#positive edges
str_real = [str(int(real[k][0])) + "_" + str(int(real[k][1])) for k in range(len(real))]
num_real = len(real) - str_real.count(str(-1)+"_"+str(-1))
set_pos = set(str_real[0: num_real])
all_pos = list(set_pos)
n_pos = len(all_pos)
#sample negative edges
all_neg = list(set(all_edge) - set_pos)
n_sampled_neg = int(n_pos * npr)
sampled_neg = random.sample(all_neg, n_sampled_neg)
#prepare for loss computing
pos = [[int(item.split("_")[0]), int(item.split("_")[1])] for item in all_pos]
neg = [[int(item.split("_")[0]), int(item.split("_")[1])] for item in sampled_neg]
pos_idx = [pos[k][0]*n_loc + pos[k][1] for k in range(n_pos)]
neg_idx = [neg[k][0]*n_loc + neg[k][1] for k in range(n_sampled_neg)]
hat_1_pos = torch.take(predicted, torch.tensor(pos_idx))
hat_1_neg = torch.take(predicted, torch.tensor(neg_idx))
hat_1 = torch.sigmoid(torch.cat((hat_1_pos, hat_1_neg)).unsqueeze(dim=0))
hat = torch.log(torch.transpose(torch.cat((1.0-hat_1, hat_1), dim=0),1,0)) #NLLLOSS
real = torch.tensor([1]*n_pos + [0]*n_sampled_neg)
loss += criterion(hat, real)
loss = loss*1.0/(batch*y_day)
return loss
#define user embeddings based on POI embeddings.
#input1: x_loc dim = (V, 200)
#input2: x_mob_batch dim = (batch, x_day, n_m, 2)
#input3: x_text_batch dim = (batch, x_day, n_t, 2)
#input4: n_user
#output: x_user dim = (batch, U, 200)
def compute_user_embedding(x_loc, x_mob_batch, x_text_batch, n_user):
x_user = torch.zeros((0, n_user, 200), device=device)
x_m_t_batch = torch.cat([x_mob_batch, x_text_batch], dim=2) #dim = (batch, x_day, n_m+n_t, 2)
batch = x_m_t_batch.size()[0]
for i in range(batch):
#initialize
user_sum_embed = torch.zeros((n_user, 200), device=device)
user_ave_embed = torch.zeros((n_user, 200), device=device)
user_count_embed, user_with_edge = [0]*n_user, list()
#update user embeddings
link_record = x_m_t_batch[i][0] #extract the first day
for link in link_record:
if link[0] != -1:
user, loc = link[0], link[1]
user_with_edge.append(user)
user_count_embed[user] = user_count_embed[user] + 1
user_sum_embed[user] = user_sum_embed[user] + x_loc[loc]
else:
break
set_user_with_edge = set(user_with_edge)
for user in set_user_with_edge:
user_ave_embed[user] = user_sum_embed[user]/user_count_embed[user]
#update the user embedding for other users with mobility records on the first day
#compute the average embedding
n_user_with_edge = len(set_user_with_edge)
ave_embedding = torch.sum(user_ave_embed, dim=0)/(1.0*n_user_with_edge)
#define the embeddings for remaining users as the average embedding
set_remain = set(range(n_user))-set_user_with_edge
dict_remain = {user:0 for user in set_remain}
for user in dict_remain:
user_ave_embed[user] = ave_embedding
#concatenate different batches
x_user = torch.cat([x_user, user_ave_embed.unsqueeze(0)],dim=0)
return x_user
#input1: x_mob_batch dim = (batch, x_day, n_m, 2)
#input2: x_text_batch dim = (batch, x_day, n_t, 2)
#inputs3,4: u_user, n_loc
#output1: x_adj dim = (batch, x_day, n_user+2*n_loc, n_user+2*n_loc)
def convert_to_adj(x_mob_batch, x_text_batch, n_user, n_loc):
time_1 = time.time()
batch, x_day = x_mob_batch.size()[0], x_mob_batch.size()[1]
adj_dim = n_user + 2*n_loc
adj = torch.zeros((batch, x_day, adj_dim, adj_dim), device=device)
for i in range(batch):
x_mob_record, x_text_record = x_mob_batch[i], x_text_batch[i]
for j in range(x_day):
x_mob_one_day, x_text_one_day = x_mob_record[j], x_text_record[j]
#extract mob edges
for link in x_mob_one_day:
if link[0] != -1:
user, loc = link[0], link[1]
n_idx = n_user + loc
adj[i][j][user][n_idx] = adj[i][j][user][n_idx] + 1
adj[i][j][n_idx][user] = adj[i][j][user][n_idx]
else:
break
#extract text edges
for link in x_text_one_day:
if link[0] != -1:
user, loc = link[0], link[1]
n_idx = n_user + n_loc + loc
adj[i][j][user][n_idx] = adj[i][j][user][n_idx] + 1
adj[i][j][n_idx][user] = adj[i][j][user][n_idx]
else:
break
return adj
#6.1: one training epoch
#output: the average loss, model
def train_epoch(model, opt, criterion, train, hyper_param_dict, y_day, npr, loss_batch_all):
time_1 = time.time()
model.train()
losses = list()
n_user, n_loc, b_s = hyper_param["n_user"], hyper_param["n_loc"], hyper_param["b_s"]
x_u_v, x_poi, train_x_mob, train_x_text, train_y_mob =\
train["u_v"].to(device), train["x_poi"].to(device), train["x_mob"],\
train["x_text"], train["y_mob"]
n = train_x_mob.size()[0]
print ("# batch: ", int(n/b_s))
for i in range(0, n-b_s, b_s):
time_1 = time.time()
x_mob_batch, x_text_batch, y_mob_batch = train_x_mob[i:i + b_s], train_x_text[i:i + b_s], train_y_mob[i:i + b_s]
opt.zero_grad()
loss = torch.zeros(1, dtype=torch.float)
x_user = compute_user_embedding(x_poi, x_mob_batch, x_text_batch, n_user) #4.
x_adj = convert_to_adj(x_mob_batch, x_text_batch, n_user, n_loc) #5.
model_output = model.run(x_u_v, x_poi, x_user.to(device), x_adj.to(device), b_s)
loss = compute_loss(model_output.cpu(), y_mob_batch, criterion, n_user, n_loc, npr) #3.
loss_batch_all.append(loss.data.numpy()[0])
loss.backward()
opt.step()
losses.append(loss.data.numpy()) # sum over batches
time2 = time.time()
if i%20 == 0:
print ("i_batch: ", i/b_s)
print ("the loss is: ", loss.data.numpy()[0])
print ("time for this batch: ", round(time2 - time_1,3))
print ("-----------------a batch ends---------------")
return sum(losses)/float(len(losses)+0.000001), model, loss_batch_all
#6.2
def train_process(train, vali, test, net, criterion, hyper_param, y_day, loss_batch_all):
e_losses_train = list()
recall_vali, recall_test, ndcg_vali, ndcg_test = list(), list(), list(), list()
l_r, n_e, b_s = hyper_param["l_r"], hyper_param["n_e"], hyper_param["b_s"]
opt = optim.Adam(net.parameters(), l_r, betas = (0.9,0.999), weight_decay = 0.0001)
opt_scheduler = torch.optim.lr_scheduler.MultiStepLR(opt, milestones=[150])
print ("# epochs: ", n_e)
print ("------------------------------------------------------------")
time_start = time.time()
no_improve_in_n = 0
#prepare for vali and test
print ("start preparing for vali and test")
vali_u_v, vali_x_poi, vali_x_user, vali_x_adj, vali_y_real = prepare_validate_test(vali, hyper_param)
print ("finish vali")
test_u_v, test_x_poi, test_x_user, test_x_adj, test_y_real = prepare_validate_test(test, hyper_param)
print ("finish test")
for i in range(n_e):
print ("i_epoch: ", i)
print ("----------------an epoch starts-------------------")
time1 = time.time()
n_train = len(train["x_mob"])
number_list = copy.copy(list(range(n_train)))
random.shuffle(number_list, random = r)
shuffle_idx = torch.tensor(number_list)
#train one epoch
train_shuffle = dict()
train_shuffle["u_v"] = train["u_v"]
train_shuffle["x_poi"], train_shuffle["x_mob"] = train["x_poi"], train["x_mob"][shuffle_idx]
train_shuffle["x_text"], train_shuffle["y_mob"] = train["x_text"][shuffle_idx], train["y_mob"][shuffle_idx]
loss, net, loss_batch_all = train_epoch(net, opt, criterion, train_shuffle, hyper_param, y_day, npr, loss_batch_all)
opt_scheduler.step()
loss = float(loss)
print ("train loss for this epoch: ", round(loss, 6))
e_losses_train.append(loss)
visual_train_loss(e_losses_train)
print ("----------------validate-------------------")
val_all_recall, val_all_ndcg, val_ave_recall, val_ave_ndcg =\
validate_test(net, hyper_param, \
vali_u_v, vali_x_poi, vali_x_user, vali_x_adj, vali_y_real, False)
print ("----------------test-------------------")
test_all_recall, test_all_ndcg, test_ave_recall, test_ave_ndcg =\
validate_test(net, hyper_param,\
test_u_v, test_x_poi, test_x_user, test_x_adj, test_y_real, False)
if len(recall_vali) > 0:
past_max = np.max(recall_vali)
else:
past_max = 0.0
recall_vali.append(val_ave_recall)
recall_test.append(test_ave_recall)
ndcg_vali.append(val_ave_ndcg)
ndcg_test.append(test_ave_ndcg)
visual_vali_test_loss(recall_vali, recall_test, ndcg_vali, ndcg_test)
#store
performance = {"recall_val": recall_vali, "recall_test": recall_test, \
"ndcg_val": ndcg_vali,"ndcg_test": ndcg_test,\
"e_losses_train": e_losses_train}
subfile = open(case + '/' + 'performance'+'.json','w')
json.dump(performance, subfile)
subfile.close()
#early stop
if val_ave_recall < past_max:
no_improve_in_n = no_improve_in_n + 1
else:
no_improve_in_n = 0
if no_improve_in_n == 30:
print ("Early stop at the " + str(i+1) + "-th epoch")
return e_losses_train, net, loss_batch_all
time2 = time.time()
print ("running time for this epoch: ", time2 - time1)
time_now = time.time()
print ("running time until now: ", time_now - time_start)
print ("-------------------------an epoch ends ---------------------------")
return e_losses_train, net, loss_batch_all
#6.3
def model_train(train, vali, test, hyper_param, x_day, y_day, member):
with torch.autograd.set_detect_anomaly(True):
loss_batch_all = list()
model = WSBiGNN(hid_dim, hid_dim_cons, x_day, member).to(device)
criterion = nn.NLLLoss()
print ("start train_process")
e_losses, trained_model, loss_batch_all = train_process(train, vali, test, model,\
criterion, hyper_param, y_day, loss_batch_all)
return e_losses, trained_model, loss_batch_all
#7.1: compute Recall@K, NDCG@K
#input1: gnn_output dim = (batch, y_day, U, V)
#input2: real_link dim = (batch, y_day, n_edge, 2)
#inputs3,4: n_user, n_loc
#input5: top_k
#output: Recall@K, NDCG@K
def compute_recall_ndcg(gnn_output, real_link, n_user, n_loc, top_k):
batch, y_day = gnn_output.size()[0], gnn_output.size()[1]
recall_all = [[0.0 for j in range(y_day)] for i in range(batch)]
ndcg_all = [[0.0 for j in range(y_day)] for i in range(batch)]
for i in range(batch):
for j in range(y_day):
recall_user, ndcg_user = {}, {}
predicted, real = gnn_output[i][j].tolist(), real_link[i][j]
#1. construct the real mobility
real_list, real_dict = {user: [] for user in range(n_user)}, {user: {} for user in range(n_user)}
for k in range(len(real)):
edge = real[k]
user, poi = int(edge[0]), int(edge[1])
if user > -1:
real_list[user].append(poi)
else:
break
for user in real_list:
real_dict[user] = set(real_list[user])
#2. compute Recall@K, NDCG@K
for user in real_dict:
real_poi = real_dict[user]
len_real_poi = len(real_poi)
if len_real_poi > 0:
predict_row = predicted[user] #[0,0,12,1,5]
largest_k_idx = np.argsort(predict_row)[::-1] #[2,4,3,1,0]
top_k_idx = largest_k_idx[0: top_k] #[2,4,3]
#compute Recall
predict_top_k = set(top_k_idx)
recall_user[user] = len(predict_top_k.intersection(real_poi))*1.0/len_real_poi
#compute NDCG
weight = [1.0/(math.log(k+2)/math.log(2.0)) for k in range(top_k)]
#denominator
if len_real_poi < top_k:
best_rank = [1.0]*len_real_poi + [0.0]*(top_k-len_real_poi)
else:
best_rank = [1.0]*top_k
#numerator
predict_rank = [0.0]* top_k
for idx in range(len(top_k_idx)):
if top_k_idx[idx] in real_poi:
predict_rank[idx] = 1.0
#NDCG
ndcg_user[user] = float(np.dot(weight, predict_rank)/np.dot(weight, best_rank))
#3. compute the average Recall@k, average NDCG@k.
recall_all[i][j] = float(np.mean(list(recall_user.values())))
ndcg_all[i][j] = float(np.mean(list(ndcg_user.values())))
ave_recall, ave_ndcg = np.mean(recall_all), np.mean(ndcg_all)
print ("ave Recall", ave_recall)
print ("ave NDCG", ave_ndcg)
return recall_all, ndcg_all, ave_recall, ave_ndcg
#7.2: evaluate the trained model on validation or test
def prepare_validate_test(vali_test, hyper_param):
n_user, n_loc = hyper_param["n_user"], hyper_param["n_loc"]
u_v, x_poi, x_mob, x_text, y_real =\
vali_test["u_v"].to(device), vali_test["x_poi"].to(device), vali_test["x_mob"].to(device), \
vali_test["x_text"].to(device), vali_test["y_mob"]
x_user = compute_user_embedding(x_poi, x_mob, x_text, n_user)
x_adj = convert_to_adj(x_mob, x_text, n_user, n_loc)
return u_v, x_poi, x_user, x_adj, y_real
def validate_test(trained_model, hyper_param, u_v, x_poi, x_user, x_adj, y_real, output=False):
n_user, n_loc = hyper_param["n_user"], hyper_param["n_loc"]
top_k, b_s = hyper_param["top_k"], y_real.size()[0]
y_hat = trained_model.run(u_v, x_poi, x_user, x_adj, b_s)
all_recall, all_ndcg, ave_recall, ave_ndcg =\
compute_recall_ndcg(y_hat.cpu(), y_real, n_user, n_loc, top_k)
if output == True:
return all_recall, all_ndcg, ave_recall, ave_ndcg, y_hat.cpu(), y_real
else:
return all_recall, all_ndcg, ave_recall, ave_ndcg
#8.1: tensorize
def tensorize(train_vali_test):
result = dict()
result["u_v"] = torch.tensor(train_vali_test["u_v"])
result["x_poi"] = torch.tensor(train_vali_test["x_poi"])
result["x_mob"] = torch.tensor(train_vali_test["x_mob"])
result["x_text"] = torch.tensor(train_vali_test["x_text"])
result["y_mob"] = torch.tensor(train_vali_test["y_mob"])
return result
#8.2: load the data
train = tensorize(json.load(open(train_path)))
vali = tensorize(json.load(open(vali_path)))
test = tensorize(json.load(open(test_path)))
sampled_user_location = json.load(open(sampled_user_location_path))
sampled_user_location["n_user"] = len(sampled_user_location["u"])
sampled_user_location["n_loc"] = len(sampled_user_location["p"])
u_list, p_list = sampled_user_location["u"], sampled_user_location["p"]
hyper_param["n_user"], hyper_param["n_loc"] = len(u_list), len(p_list)
#supernode
member_dict = json.load(open(member_path + "member_" + case + ".json"))
#sg, s_ng, ns_g, ns_ng
member = torch.tensor([member_dict["s_g"], member_dict["s_ng"],\
member_dict["ns_g"], member_dict["ns_ng"]], device=device)
#8.3: model
e_losses, trained_model, loss_batch_all = model_train(train, vali, test, hyper_param,\
x_day, y_day, member)
start train_process # epochs: 200 ------------------------------------------------------------ start preparing for vali and test finish vali finish test i_epoch: 0 ----------------an epoch starts------------------- # batch: 63 i_batch: 0.0 the loss is: 6.4551945 time for this batch: 1.543 -----------------a batch ends--------------- i_batch: 10.0 the loss is: 3.755136 time for this batch: 0.69 -----------------a batch ends--------------- i_batch: 20.0 the loss is: 2.5719948 time for this batch: 0.863 -----------------a batch ends--------------- i_batch: 30.0 the loss is: 1.9302506 time for this batch: 0.752 -----------------a batch ends--------------- i_batch: 40.0 the loss is: 1.5922208 time for this batch: 0.841 -----------------a batch ends--------------- i_batch: 50.0 the loss is: 1.3612849 time for this batch: 0.815 -----------------a batch ends--------------- i_batch: 60.0 the loss is: 1.1941475 time for this batch: 0.733 -----------------a batch ends--------------- train loss for this epoch: 2.461898
----------------validate------------------- ave Recall 0.05368904185149889 ave NDCG 0.0337704240876557 ----------------test------------------- ave Recall 0.054915484236194356 ave NDCG 0.035655956352420165
running time for this epoch: 57.43118739128113 running time until now: 138.89907503128052 -------------------------an epoch ends --------------------------- i_epoch: 1 ----------------an epoch starts------------------- # batch: 63 i_batch: 0.0 the loss is: 1.1746511 time for this batch: 0.7 -----------------a batch ends--------------- i_batch: 10.0 the loss is: 1.080836 time for this batch: 0.921 -----------------a batch ends--------------- i_batch: 20.0 the loss is: 1.0046064 time for this batch: 0.896 -----------------a batch ends--------------- i_batch: 30.0 the loss is: 0.94327974 time for this batch: 0.887 -----------------a batch ends--------------- i_batch: 40.0 the loss is: 0.897148 time for this batch: 0.774 -----------------a batch ends--------------- i_batch: 50.0 the loss is: 0.8503902 time for this batch: 0.677 -----------------a batch ends--------------- i_batch: 60.0 the loss is: 0.805946 time for this batch: 0.708 -----------------a batch ends--------------- train loss for this epoch: 0.957759
----------------validate------------------- ave Recall 0.05610499590587491 ave NDCG 0.035701805382371825 ----------------test------------------- ave Recall 0.04938265198985753 ave NDCG 0.030326825385713338
running time for this epoch: 55.80727291107178 running time until now: 194.70639157295227 -------------------------an epoch ends --------------------------- i_epoch: 2 ----------------an epoch starts------------------- # batch: 63 i_batch: 0.0 the loss is: 0.7980334 time for this batch: 0.812 -----------------a batch ends--------------- i_batch: 10.0 the loss is: 0.753665 time for this batch: 0.839 -----------------a batch ends--------------- i_batch: 20.0 the loss is: 0.7115643 time for this batch: 0.921 -----------------a batch ends--------------- i_batch: 30.0 the loss is: 0.66628265 time for this batch: 0.734 -----------------a batch ends--------------- i_batch: 40.0 the loss is: 0.620415 time for this batch: 0.771 -----------------a batch ends--------------- i_batch: 50.0 the loss is: 0.56804866 time for this batch: 0.83 -----------------a batch ends--------------- i_batch: 60.0 the loss is: 0.51838344 time for this batch: 0.887 -----------------a batch ends--------------- train loss for this epoch: 0.661197
----------------validate------------------- ave Recall 0.288437187068438 ave NDCG 0.23156701137572863 ----------------test------------------- ave Recall 0.29041033676236844 ave NDCG 0.2376682720280735
running time for this epoch: 54.376497983932495 running time until now: 249.08293318748474 -------------------------an epoch ends --------------------------- i_epoch: 3 ----------------an epoch starts------------------- # batch: 63 i_batch: 0.0 the loss is: 0.5074045 time for this batch: 0.634 -----------------a batch ends--------------- i_batch: 10.0 the loss is: 0.46755174 time for this batch: 0.687 -----------------a batch ends--------------- i_batch: 20.0 the loss is: 0.44130313 time for this batch: 0.85 -----------------a batch ends--------------- i_batch: 30.0 the loss is: 0.39473566 time for this batch: 0.642 -----------------a batch ends--------------- i_batch: 40.0 the loss is: 0.36091825 time for this batch: 0.832 -----------------a batch ends--------------- i_batch: 50.0 the loss is: 0.35502803 time for this batch: 0.789 -----------------a batch ends--------------- i_batch: 60.0 the loss is: 0.3492634 time for this batch: 0.77 -----------------a batch ends--------------- train loss for this epoch: 0.405487
----------------validate------------------- ave Recall 0.3305790774085357 ave NDCG 0.2750656450922976 ----------------test------------------- ave Recall 0.34476933067015003 ave NDCG 0.2811795565622066
running time for this epoch: 53.84571123123169 running time until now: 302.9286868572235 -------------------------an epoch ends --------------------------- i_epoch: 4 ----------------an epoch starts------------------- # batch: 63 i_batch: 0.0 the loss is: 0.34005392 time for this batch: 0.671 -----------------a batch ends--------------- i_batch: 10.0 the loss is: 0.33186483 time for this batch: 0.824 -----------------a batch ends--------------- i_batch: 20.0 the loss is: 0.30827478 time for this batch: 0.774 -----------------a batch ends--------------- i_batch: 30.0 the loss is: 0.30169624 time for this batch: 0.789 -----------------a batch ends--------------- i_batch: 40.0 the loss is: 0.3071944 time for this batch: 0.689 -----------------a batch ends--------------- i_batch: 50.0 the loss is: 0.27922165 time for this batch: 0.751 -----------------a batch ends--------------- i_batch: 60.0 the loss is: 0.28880686 time for this batch: 0.847 -----------------a batch ends--------------- train loss for this epoch: 0.305799
----------------validate------------------- ave Recall 0.40879327315960223 ave NDCG 0.34427866277067065 ----------------test------------------- ave Recall 0.3776212176272128 ave NDCG 0.3137447478277305
running time for this epoch: 55.4896023273468 running time until now: 358.4183394908905 -------------------------an epoch ends --------------------------- i_epoch: 5 ----------------an epoch starts------------------- # batch: 63 i_batch: 0.0 the loss is: 0.27199918 time for this batch: 0.707 -----------------a batch ends--------------- i_batch: 10.0 the loss is: 0.28424206 time for this batch: 0.76 -----------------a batch ends--------------- i_batch: 20.0 the loss is: 0.27821907 time for this batch: 0.837 -----------------a batch ends--------------- i_batch: 30.0 the loss is: 0.28847945 time for this batch: 0.846 -----------------a batch ends--------------- i_batch: 40.0 the loss is: 0.2569798 time for this batch: 0.839 -----------------a batch ends--------------- i_batch: 50.0 the loss is: 0.24410877 time for this batch: 0.809 -----------------a batch ends--------------- i_batch: 60.0 the loss is: 0.24174228 time for this batch: 0.847 -----------------a batch ends--------------- train loss for this epoch: 0.26704
----------------validate------------------- ave Recall 0.5000978296428309 ave NDCG 0.4307470140387966 ----------------test------------------- ave Recall 0.4604443742362477 ave NDCG 0.3892602843378973
running time for this epoch: 56.5573947429657 running time until now: 414.975781917572 -------------------------an epoch ends --------------------------- i_epoch: 6 ----------------an epoch starts------------------- # batch: 63 i_batch: 0.0 the loss is: 0.2384956 time for this batch: 0.76 -----------------a batch ends--------------- i_batch: 10.0 the loss is: 0.23460299 time for this batch: 0.709 -----------------a batch ends--------------- i_batch: 20.0 the loss is: 0.23878485 time for this batch: 0.842 -----------------a batch ends--------------- i_batch: 30.0 the loss is: 0.23671111 time for this batch: 0.686 -----------------a batch ends--------------- i_batch: 40.0 the loss is: 0.23429698 time for this batch: 0.597 -----------------a batch ends--------------- i_batch: 50.0 the loss is: 0.21659416 time for this batch: 0.891 -----------------a batch ends--------------- i_batch: 60.0 the loss is: 0.23017412 time for this batch: 0.897 -----------------a batch ends--------------- train loss for this epoch: 0.237792
----------------validate------------------- ave Recall 0.5607250803927045 ave NDCG 0.48509447639224107 ----------------test------------------- ave Recall 0.5274689032710835 ave NDCG 0.4490028107729718
running time for this epoch: 53.61614942550659 running time until now: 468.59197640419006 -------------------------an epoch ends --------------------------- i_epoch: 7 ----------------an epoch starts------------------- # batch: 63 i_batch: 0.0 the loss is: 0.21872656 time for this batch: 0.638 -----------------a batch ends--------------- i_batch: 10.0 the loss is: 0.22193438 time for this batch: 0.671 -----------------a batch ends--------------- i_batch: 20.0 the loss is: 0.21363527 time for this batch: 0.856 -----------------a batch ends--------------- i_batch: 30.0 the loss is: 0.22720781 time for this batch: 0.75 -----------------a batch ends--------------- i_batch: 40.0 the loss is: 0.23271182 time for this batch: 0.93 -----------------a batch ends--------------- i_batch: 50.0 the loss is: 0.22286707 time for this batch: 0.791 -----------------a batch ends--------------- i_batch: 60.0 the loss is: 0.21802622 time for this batch: 0.69 -----------------a batch ends--------------- train loss for this epoch: 0.217623
----------------validate------------------- ave Recall 0.6071526048866328 ave NDCG 0.5223009693597155 ----------------test------------------- ave Recall 0.5763561720289139 ave NDCG 0.491704560799077
running time for this epoch: 53.2183198928833 running time until now: 521.8103394508362 -------------------------an epoch ends --------------------------- i_epoch: 8 ----------------an epoch starts------------------- # batch: 63 i_batch: 0.0 the loss is: 0.20270714 time for this batch: 0.644 -----------------a batch ends--------------- i_batch: 10.0 the loss is: 0.21831611 time for this batch: 0.868 -----------------a batch ends--------------- i_batch: 20.0 the loss is: 0.19441384 time for this batch: 0.824 -----------------a batch ends--------------- i_batch: 30.0 the loss is: 0.20143858 time for this batch: 0.811 -----------------a batch ends--------------- i_batch: 40.0 the loss is: 0.18687466 time for this batch: 0.801 -----------------a batch ends--------------- i_batch: 50.0 the loss is: 0.19653967 time for this batch: 0.892 -----------------a batch ends--------------- i_batch: 60.0 the loss is: 0.20029435 time for this batch: 0.681 -----------------a batch ends--------------- train loss for this epoch: 0.20372
----------------validate------------------- ave Recall 0.6311408379853402 ave NDCG 0.5415007154841043 ----------------test------------------- ave Recall 0.6076228670842508 ave NDCG 0.5182579165007891
running time for this epoch: 53.49553442001343 running time until now: 575.3059256076813 -------------------------an epoch ends --------------------------- i_epoch: 9 ----------------an epoch starts------------------- # batch: 63 i_batch: 0.0 the loss is: 0.19944397 time for this batch: 0.759 -----------------a batch ends--------------- i_batch: 10.0 the loss is: 0.18174942 time for this batch: 0.794 -----------------a batch ends--------------- i_batch: 20.0 the loss is: 0.2077645 time for this batch: 0.797 -----------------a batch ends--------------- i_batch: 30.0 the loss is: 0.18548653 time for this batch: 0.886 -----------------a batch ends--------------- i_batch: 40.0 the loss is: 0.20753393 time for this batch: 0.895 -----------------a batch ends--------------- i_batch: 50.0 the loss is: 0.19007814 time for this batch: 0.781 -----------------a batch ends--------------- i_batch: 60.0 the loss is: 0.18403035 time for this batch: 0.845 -----------------a batch ends--------------- train loss for this epoch: 0.193176
----------------validate------------------- ave Recall 0.6448427629558929 ave NDCG 0.5526212653612738 ----------------test------------------- ave Recall 0.6237174572719483 ave NDCG 0.5307814694638581
running time for this epoch: 55.263845443725586 running time until now: 630.5698175430298 -------------------------an epoch ends --------------------------- i_epoch: 10 ----------------an epoch starts------------------- # batch: 63 i_batch: 0.0 the loss is: 0.18055405 time for this batch: 0.706 -----------------a batch ends--------------- i_batch: 10.0 the loss is: 0.18223241 time for this batch: 0.845 -----------------a batch ends--------------- i_batch: 20.0 the loss is: 0.19415668 time for this batch: 0.87 -----------------a batch ends--------------- i_batch: 30.0 the loss is: 0.17730601 time for this batch: 0.794 -----------------a batch ends--------------- i_batch: 40.0 the loss is: 0.17956828 time for this batch: 0.797 -----------------a batch ends--------------- i_batch: 50.0 the loss is: 0.19472349 time for this batch: 0.845 -----------------a batch ends--------------- i_batch: 60.0 the loss is: 0.17059126 time for this batch: 0.786 -----------------a batch ends--------------- train loss for this epoch: 0.185011
----------------validate------------------- ave Recall 0.6514761257453677 ave NDCG 0.5581900832816792 ----------------test------------------- ave Recall 0.6367385080140016 ave NDCG 0.5399485186378935
running time for this epoch: 56.95112133026123 running time until now: 687.5209803581238 -------------------------an epoch ends --------------------------- i_epoch: 11 ----------------an epoch starts------------------- # batch: 63 i_batch: 0.0 the loss is: 0.18795809 time for this batch: 0.656 -----------------a batch ends--------------- i_batch: 10.0 the loss is: 0.17791082 time for this batch: 0.814 -----------------a batch ends--------------- i_batch: 20.0 the loss is: 0.16275384 time for this batch: 0.858 -----------------a batch ends--------------- i_batch: 30.0 the loss is: 0.17775634 time for this batch: 0.934 -----------------a batch ends--------------- i_batch: 40.0 the loss is: 0.19743541 time for this batch: 0.841 -----------------a batch ends--------------- i_batch: 50.0 the loss is: 0.17691952 time for this batch: 0.874 -----------------a batch ends--------------- i_batch: 60.0 the loss is: 0.19490728 time for this batch: 0.883 -----------------a batch ends--------------- train loss for this epoch: 0.179005
----------------validate------------------- ave Recall 0.65586641176295 ave NDCG 0.5637920019408097 ----------------test------------------- ave Recall 0.6492148809490397 ave NDCG 0.5468288685817475
running time for this epoch: 56.003705739974976 running time until now: 743.5247311592102 -------------------------an epoch ends --------------------------- i_epoch: 12 ----------------an epoch starts------------------- # batch: 63 i_batch: 0.0 the loss is: 0.19013026 time for this batch: 0.717 -----------------a batch ends--------------- i_batch: 10.0 the loss is: 0.16436192 time for this batch: 0.996 -----------------a batch ends--------------- i_batch: 20.0 the loss is: 0.17698018 time for this batch: 0.752 -----------------a batch ends--------------- i_batch: 30.0 the loss is: 0.1722727 time for this batch: 0.853 -----------------a batch ends--------------- i_batch: 40.0 the loss is: 0.16646677 time for this batch: 0.715 -----------------a batch ends--------------- i_batch: 50.0 the loss is: 0.17331076 time for this batch: 0.741 -----------------a batch ends--------------- i_batch: 60.0 the loss is: 0.16032392 time for this batch: 0.791 -----------------a batch ends--------------- train loss for this epoch: 0.17184
----------------validate------------------- ave Recall 0.6579758391602053 ave NDCG 0.563541572720673 ----------------test------------------- ave Recall 0.649355533314717 ave NDCG 0.5465566331214913
running time for this epoch: 54.90040874481201 running time until now: 798.4251832962036 -------------------------an epoch ends --------------------------- i_epoch: 13 ----------------an epoch starts------------------- # batch: 63 i_batch: 0.0 the loss is: 0.17815803 time for this batch: 0.722 -----------------a batch ends--------------- i_batch: 10.0 the loss is: 0.16826315 time for this batch: 0.723 -----------------a batch ends--------------- i_batch: 20.0 the loss is: 0.15520367 time for this batch: 0.672 -----------------a batch ends--------------- i_batch: 30.0 the loss is: 0.16384402 time for this batch: 0.813 -----------------a batch ends--------------- i_batch: 40.0 the loss is: 0.17958632 time for this batch: 0.822 -----------------a batch ends--------------- i_batch: 50.0 the loss is: 0.1654749 time for this batch: 0.798 -----------------a batch ends--------------- i_batch: 60.0 the loss is: 0.17442921 time for this batch: 0.712 -----------------a batch ends--------------- train loss for this epoch: 0.168378
----------------validate------------------- ave Recall 0.6628545417698173 ave NDCG 0.5644505952278138 ----------------test------------------- ave Recall 0.6565384762610394 ave NDCG 0.5514360451129652
running time for this epoch: 55.094356060028076 running time until now: 853.5195815563202 -------------------------an epoch ends --------------------------- i_epoch: 14 ----------------an epoch starts------------------- # batch: 63 i_batch: 0.0 the loss is: 0.15213479 time for this batch: 0.663 -----------------a batch ends--------------- i_batch: 10.0 the loss is: 0.16763364 time for this batch: 0.786 -----------------a batch ends--------------- i_batch: 20.0 the loss is: 0.15441036 time for this batch: 0.649 -----------------a batch ends--------------- i_batch: 30.0 the loss is: 0.16156323 time for this batch: 0.856 -----------------a batch ends--------------- i_batch: 40.0 the loss is: 0.1599458 time for this batch: 0.719 -----------------a batch ends--------------- i_batch: 50.0 the loss is: 0.16529642 time for this batch: 0.872 -----------------a batch ends--------------- i_batch: 60.0 the loss is: 0.16771287 time for this batch: 0.813 -----------------a batch ends--------------- train loss for this epoch: 0.164242
----------------validate------------------- ave Recall 0.6663954837965447 ave NDCG 0.5663363253792901 ----------------test------------------- ave Recall 0.6551637736995234 ave NDCG 0.5501209318662446
running time for this epoch: 55.094462156295776 running time until now: 908.6140856742859 -------------------------an epoch ends --------------------------- i_epoch: 15 ----------------an epoch starts------------------- # batch: 63 i_batch: 0.0 the loss is: 0.16138297 time for this batch: 0.791 -----------------a batch ends--------------- i_batch: 10.0 the loss is: 0.15650374 time for this batch: 0.767 -----------------a batch ends--------------- i_batch: 20.0 the loss is: 0.18089455 time for this batch: 0.88 -----------------a batch ends--------------- i_batch: 30.0 the loss is: 0.15433237 time for this batch: 0.861 -----------------a batch ends--------------- i_batch: 40.0 the loss is: 0.16972646 time for this batch: 0.839 -----------------a batch ends--------------- i_batch: 50.0 the loss is: 0.16092125 time for this batch: 0.845 -----------------a batch ends--------------- i_batch: 60.0 the loss is: 0.15809527 time for this batch: 0.78 -----------------a batch ends--------------- train loss for this epoch: 0.161476
----------------validate------------------- ave Recall 0.6660603634169504 ave NDCG 0.5646978412442254 ----------------test------------------- ave Recall 0.661612517781042 ave NDCG 0.5537280602072755
running time for this epoch: 56.313440799713135 running time until now: 964.9275758266449 -------------------------an epoch ends --------------------------- i_epoch: 16 ----------------an epoch starts------------------- # batch: 63 i_batch: 0.0 the loss is: 0.1485593 time for this batch: 0.684 -----------------a batch ends--------------- i_batch: 10.0 the loss is: 0.15503794 time for this batch: 0.779 -----------------a batch ends--------------- i_batch: 20.0 the loss is: 0.153061 time for this batch: 0.726 -----------------a batch ends--------------- i_batch: 30.0 the loss is: 0.16278552 time for this batch: 0.793 -----------------a batch ends--------------- i_batch: 40.0 the loss is: 0.14916025 time for this batch: 0.799 -----------------a batch ends--------------- i_batch: 50.0 the loss is: 0.1471301 time for this batch: 0.881 -----------------a batch ends--------------- i_batch: 60.0 the loss is: 0.15488176 time for this batch: 0.837 -----------------a batch ends--------------- train loss for this epoch: 0.159903
----------------validate------------------- ave Recall 0.6742667199868164 ave NDCG 0.5709701057491189 ----------------test------------------- ave Recall 0.6544583394083653 ave NDCG 0.547849004484093
running time for this epoch: 55.33725905418396 running time until now: 1020.2648825645447 -------------------------an epoch ends --------------------------- i_epoch: 17 ----------------an epoch starts------------------- # batch: 63 i_batch: 0.0 the loss is: 0.14612535 time for this batch: 0.683 -----------------a batch ends--------------- i_batch: 10.0 the loss is: 0.15479812 time for this batch: 0.828 -----------------a batch ends--------------- i_batch: 20.0 the loss is: 0.1614201 time for this batch: 0.737 -----------------a batch ends--------------- i_batch: 30.0 the loss is: 0.14187014 time for this batch: 0.734 -----------------a batch ends--------------- i_batch: 40.0 the loss is: 0.15782937 time for this batch: 0.865 -----------------a batch ends--------------- i_batch: 50.0 the loss is: 0.1668356 time for this batch: 0.727 -----------------a batch ends--------------- i_batch: 60.0 the loss is: 0.158752 time for this batch: 0.732 -----------------a batch ends--------------- train loss for this epoch: 0.155843
----------------validate------------------- ave Recall 0.6670180152553595 ave NDCG 0.5678688704716611 ----------------test------------------- ave Recall 0.658022389954054 ave NDCG 0.5508294766967299
running time for this epoch: 54.16564893722534 running time until now: 1074.4305768013 -------------------------an epoch ends --------------------------- i_epoch: 18 ----------------an epoch starts------------------- # batch: 63 i_batch: 0.0 the loss is: 0.15573815 time for this batch: 0.793 -----------------a batch ends--------------- i_batch: 10.0 the loss is: 0.13589683 time for this batch: 0.743 -----------------a batch ends--------------- i_batch: 20.0 the loss is: 0.15623707 time for this batch: 0.775 -----------------a batch ends--------------- i_batch: 30.0 the loss is: 0.1355663 time for this batch: 0.796 -----------------a batch ends--------------- i_batch: 40.0 the loss is: 0.17480075 time for this batch: 0.818 -----------------a batch ends--------------- i_batch: 50.0 the loss is: 0.15791455 time for this batch: 0.814 -----------------a batch ends--------------- i_batch: 60.0 the loss is: 0.14965034 time for this batch: 0.887 -----------------a batch ends--------------- train loss for this epoch: 0.154104
----------------validate------------------- ave Recall 0.6702468612741106 ave NDCG 0.5715092906071271 ----------------test------------------- ave Recall 0.6561338566045861 ave NDCG 0.5512273137397495
running time for this epoch: 54.054386377334595 running time until now: 1128.4850380420685 -------------------------an epoch ends --------------------------- i_epoch: 19 ----------------an epoch starts------------------- # batch: 63 i_batch: 0.0 the loss is: 0.15692846 time for this batch: 1.039 -----------------a batch ends--------------- i_batch: 10.0 the loss is: 0.15028283 time for this batch: 0.853 -----------------a batch ends--------------- i_batch: 20.0 the loss is: 0.16471505 time for this batch: 0.772 -----------------a batch ends--------------- i_batch: 30.0 the loss is: 0.16425753 time for this batch: 0.698 -----------------a batch ends--------------- i_batch: 40.0 the loss is: 0.14109239 time for this batch: 0.893 -----------------a batch ends--------------- i_batch: 50.0 the loss is: 0.14754628 time for this batch: 0.639 -----------------a batch ends--------------- i_batch: 60.0 the loss is: 0.16674279 time for this batch: 0.676 -----------------a batch ends--------------- train loss for this epoch: 0.152401
----------------validate------------------- ave Recall 0.6710969353208145 ave NDCG 0.5698893528451427 ----------------test------------------- ave Recall 0.6547153788248964 ave NDCG 0.5487324362395171
running time for this epoch: 51.35201382637024 running time until now: 1179.8371176719666 -------------------------an epoch ends --------------------------- i_epoch: 20 ----------------an epoch starts------------------- # batch: 63 i_batch: 0.0 the loss is: 0.16082115 time for this batch: 0.722 -----------------a batch ends--------------- i_batch: 10.0 the loss is: 0.1491655 time for this batch: 0.745 -----------------a batch ends--------------- i_batch: 20.0 the loss is: 0.14060366 time for this batch: 0.651 -----------------a batch ends--------------- i_batch: 30.0 the loss is: 0.13469094 time for this batch: 0.719 -----------------a batch ends--------------- i_batch: 40.0 the loss is: 0.15780821 time for this batch: 0.745 -----------------a batch ends--------------- i_batch: 50.0 the loss is: 0.16266394 time for this batch: 0.764 -----------------a batch ends--------------- i_batch: 60.0 the loss is: 0.14675513 time for this batch: 0.649 -----------------a batch ends--------------- train loss for this epoch: 0.150565
----------------validate------------------- ave Recall 0.6716183401208135 ave NDCG 0.5702700984657088 ----------------test------------------- ave Recall 0.6590191213975873 ave NDCG 0.5526714469568244
running time for this epoch: 48.604774951934814 running time until now: 1228.4419338703156 -------------------------an epoch ends --------------------------- i_epoch: 21 ----------------an epoch starts------------------- # batch: 63 i_batch: 0.0 the loss is: 0.13249636 time for this batch: 0.662 -----------------a batch ends--------------- i_batch: 10.0 the loss is: 0.15219894 time for this batch: 0.711 -----------------a batch ends--------------- i_batch: 20.0 the loss is: 0.15665156 time for this batch: 0.767 -----------------a batch ends--------------- i_batch: 30.0 the loss is: 0.14776511 time for this batch: 0.753 -----------------a batch ends--------------- i_batch: 40.0 the loss is: 0.1588685 time for this batch: 0.706 -----------------a batch ends--------------- i_batch: 50.0 the loss is: 0.16633266 time for this batch: 0.797 -----------------a batch ends--------------- i_batch: 60.0 the loss is: 0.15496787 time for this batch: 0.732 -----------------a batch ends--------------- train loss for this epoch: 0.149046
----------------validate------------------- ave Recall 0.6689290437496777 ave NDCG 0.5684750941271486 ----------------test------------------- ave Recall 0.6568107704434438 ave NDCG 0.5482115248863947
running time for this epoch: 50.13195753097534 running time until now: 1278.5739486217499 -------------------------an epoch ends --------------------------- i_epoch: 22 ----------------an epoch starts------------------- # batch: 63 i_batch: 0.0 the loss is: 0.14911914 time for this batch: 0.807 -----------------a batch ends--------------- i_batch: 10.0 the loss is: 0.13526687 time for this batch: 1.047 -----------------a batch ends--------------- i_batch: 20.0 the loss is: 0.1565008 time for this batch: 0.615 -----------------a batch ends--------------- i_batch: 30.0 the loss is: 0.14187005 time for this batch: 0.971 -----------------a batch ends--------------- i_batch: 40.0 the loss is: 0.14242068 time for this batch: 0.705 -----------------a batch ends--------------- i_batch: 50.0 the loss is: 0.15078694 time for this batch: 0.739 -----------------a batch ends--------------- i_batch: 60.0 the loss is: 0.1447745 time for this batch: 0.778 -----------------a batch ends--------------- train loss for this epoch: 0.149391
----------------validate------------------- ave Recall 0.6704827483702939 ave NDCG 0.5694171231785216 ----------------test------------------- ave Recall 0.6579665222705497 ave NDCG 0.5486791750842369
running time for this epoch: 53.281179666519165 running time until now: 1331.855176448822 -------------------------an epoch ends --------------------------- i_epoch: 23 ----------------an epoch starts------------------- # batch: 63 i_batch: 0.0 the loss is: 0.14413916 time for this batch: 0.831 -----------------a batch ends--------------- i_batch: 10.0 the loss is: 0.15666679 time for this batch: 0.661 -----------------a batch ends--------------- i_batch: 20.0 the loss is: 0.15121913 time for this batch: 0.681 -----------------a batch ends--------------- i_batch: 30.0 the loss is: 0.14237258 time for this batch: 0.962 -----------------a batch ends--------------- i_batch: 40.0 the loss is: 0.14461538 time for this batch: 0.779 -----------------a batch ends--------------- i_batch: 50.0 the loss is: 0.15344039 time for this batch: 0.869 -----------------a batch ends--------------- i_batch: 60.0 the loss is: 0.15378663 time for this batch: 0.891 -----------------a batch ends--------------- train loss for this epoch: 0.148349
----------------validate------------------- ave Recall 0.6734282881001176 ave NDCG 0.568696690808703 ----------------test------------------- ave Recall 0.6543316594430627 ave NDCG 0.5473988905460261
running time for this epoch: 53.04296946525574 running time until now: 1384.8982093334198 -------------------------an epoch ends --------------------------- i_epoch: 24 ----------------an epoch starts------------------- # batch: 63 i_batch: 0.0 the loss is: 0.14112756 time for this batch: 0.875 -----------------a batch ends--------------- i_batch: 10.0 the loss is: 0.12669885 time for this batch: 0.643 -----------------a batch ends--------------- i_batch: 20.0 the loss is: 0.13849351 time for this batch: 0.661 -----------------a batch ends--------------- i_batch: 30.0 the loss is: 0.15585722 time for this batch: 0.762 -----------------a batch ends--------------- i_batch: 40.0 the loss is: 0.14807087 time for this batch: 0.701 -----------------a batch ends--------------- i_batch: 50.0 the loss is: 0.16001497 time for this batch: 0.838 -----------------a batch ends--------------- i_batch: 60.0 the loss is: 0.13632245 time for this batch: 0.745 -----------------a batch ends--------------- train loss for this epoch: 0.146554
----------------validate------------------- ave Recall 0.6749379364892568 ave NDCG 0.5732173118275624 ----------------test------------------- ave Recall 0.6544711961237198 ave NDCG 0.5488939730941818
running time for this epoch: 53.21556782722473 running time until now: 1438.1138439178467 -------------------------an epoch ends --------------------------- i_epoch: 25 ----------------an epoch starts------------------- # batch: 63 i_batch: 0.0 the loss is: 0.14850679 time for this batch: 0.892 -----------------a batch ends--------------- i_batch: 10.0 the loss is: 0.13789146 time for this batch: 0.789 -----------------a batch ends--------------- i_batch: 20.0 the loss is: 0.13301235 time for this batch: 0.741 -----------------a batch ends--------------- i_batch: 30.0 the loss is: 0.13608257 time for this batch: 0.708 -----------------a batch ends--------------- i_batch: 40.0 the loss is: 0.14917874 time for this batch: 0.601 -----------------a batch ends--------------- i_batch: 50.0 the loss is: 0.14423673 time for this batch: 0.816 -----------------a batch ends--------------- i_batch: 60.0 the loss is: 0.15719259 time for this batch: 0.826 -----------------a batch ends--------------- train loss for this epoch: 0.145543
----------------validate------------------- ave Recall 0.6707103375765268 ave NDCG 0.5682815113069427 ----------------test------------------- ave Recall 0.6569985446473618 ave NDCG 0.5500438299470252
running time for this epoch: 51.31193923950195 running time until now: 1489.4258286952972 -------------------------an epoch ends --------------------------- i_epoch: 26 ----------------an epoch starts------------------- # batch: 63 i_batch: 0.0 the loss is: 0.13950372 time for this batch: 0.644 -----------------a batch ends--------------- i_batch: 10.0 the loss is: 0.13202007 time for this batch: 0.715 -----------------a batch ends--------------- i_batch: 20.0 the loss is: 0.16440617 time for this batch: 0.754 -----------------a batch ends--------------- i_batch: 30.0 the loss is: 0.15478985 time for this batch: 0.705 -----------------a batch ends--------------- i_batch: 40.0 the loss is: 0.1388107 time for this batch: 0.68 -----------------a batch ends--------------- i_batch: 50.0 the loss is: 0.14053532 time for this batch: 0.645 -----------------a batch ends--------------- i_batch: 60.0 the loss is: 0.14076677 time for this batch: 0.651 -----------------a batch ends--------------- train loss for this epoch: 0.145688
----------------validate------------------- ave Recall 0.6641812044147309 ave NDCG 0.5647445121866982 ----------------test------------------- ave Recall 0.6578042398363724 ave NDCG 0.5502917261982471
running time for this epoch: 51.048216342926025 running time until now: 1540.4741237163544 -------------------------an epoch ends --------------------------- i_epoch: 27 ----------------an epoch starts------------------- # batch: 63 i_batch: 0.0 the loss is: 0.14600506 time for this batch: 0.806 -----------------a batch ends--------------- i_batch: 10.0 the loss is: 0.1290971 time for this batch: 0.903 -----------------a batch ends--------------- i_batch: 20.0 the loss is: 0.13217218 time for this batch: 0.68 -----------------a batch ends--------------- i_batch: 30.0 the loss is: 0.14549771 time for this batch: 0.731 -----------------a batch ends--------------- i_batch: 40.0 the loss is: 0.14311382 time for this batch: 0.727 -----------------a batch ends--------------- i_batch: 50.0 the loss is: 0.1460993 time for this batch: 0.911 -----------------a batch ends--------------- i_batch: 60.0 the loss is: 0.1363998 time for this batch: 0.721 -----------------a batch ends--------------- train loss for this epoch: 0.145357
----------------validate------------------- ave Recall 0.6697085140655687 ave NDCG 0.5674219870388759 ----------------test------------------- ave Recall 0.6550733133325539 ave NDCG 0.5463233977697902
running time for this epoch: 53.98778319358826 running time until now: 1594.461982011795 -------------------------an epoch ends --------------------------- i_epoch: 28 ----------------an epoch starts------------------- # batch: 63 i_batch: 0.0 the loss is: 0.15203127 time for this batch: 0.698 -----------------a batch ends--------------- i_batch: 10.0 the loss is: 0.13743782 time for this batch: 0.664 -----------------a batch ends--------------- i_batch: 20.0 the loss is: 0.12231363 time for this batch: 0.671 -----------------a batch ends--------------- i_batch: 30.0 the loss is: 0.14454755 time for this batch: 0.919 -----------------a batch ends--------------- i_batch: 40.0 the loss is: 0.13937405 time for this batch: 0.849 -----------------a batch ends--------------- i_batch: 50.0 the loss is: 0.15381551 time for this batch: 0.852 -----------------a batch ends--------------- i_batch: 60.0 the loss is: 0.14735875 time for this batch: 0.602 -----------------a batch ends--------------- train loss for this epoch: 0.143264
----------------validate------------------- ave Recall 0.6695700685586188 ave NDCG 0.5661091881195577 ----------------test------------------- ave Recall 0.6505998630066977 ave NDCG 0.5458074293108086
running time for this epoch: 53.51718521118164 running time until now: 1647.9792213439941 -------------------------an epoch ends --------------------------- i_epoch: 29 ----------------an epoch starts------------------- # batch: 63 i_batch: 0.0 the loss is: 0.12664238 time for this batch: 0.756 -----------------a batch ends--------------- i_batch: 10.0 the loss is: 0.14315107 time for this batch: 0.762 -----------------a batch ends--------------- i_batch: 20.0 the loss is: 0.12930563 time for this batch: 0.774 -----------------a batch ends--------------- i_batch: 30.0 the loss is: 0.13590772 time for this batch: 0.654 -----------------a batch ends--------------- i_batch: 40.0 the loss is: 0.13466127 time for this batch: 0.586 -----------------a batch ends--------------- i_batch: 50.0 the loss is: 0.13155152 time for this batch: 0.656 -----------------a batch ends--------------- i_batch: 60.0 the loss is: 0.14609787 time for this batch: 0.782 -----------------a batch ends--------------- train loss for this epoch: 0.143164
----------------validate------------------- ave Recall 0.671848504836634 ave NDCG 0.567988886854256 ----------------test------------------- ave Recall 0.6590493431774357 ave NDCG 0.5506938034998144
running time for this epoch: 50.9627902507782 running time until now: 1698.9420669078827 -------------------------an epoch ends --------------------------- i_epoch: 30 ----------------an epoch starts------------------- # batch: 63 i_batch: 0.0 the loss is: 0.13325784 time for this batch: 0.85 -----------------a batch ends--------------- i_batch: 10.0 the loss is: 0.13510136 time for this batch: 0.706 -----------------a batch ends--------------- i_batch: 20.0 the loss is: 0.14898752 time for this batch: 0.637 -----------------a batch ends--------------- i_batch: 30.0 the loss is: 0.154565 time for this batch: 0.863 -----------------a batch ends--------------- i_batch: 40.0 the loss is: 0.13793293 time for this batch: 0.872 -----------------a batch ends--------------- i_batch: 50.0 the loss is: 0.16277137 time for this batch: 0.598 -----------------a batch ends--------------- i_batch: 60.0 the loss is: 0.14514935 time for this batch: 0.745 -----------------a batch ends--------------- train loss for this epoch: 0.142206
----------------validate------------------- ave Recall 0.6682384563816616 ave NDCG 0.56501555904148 ----------------test------------------- ave Recall 0.6605441423149919 ave NDCG 0.5472989992134276
running time for this epoch: 51.39018678665161 running time until now: 1750.3323166370392 -------------------------an epoch ends --------------------------- i_epoch: 31 ----------------an epoch starts------------------- # batch: 63 i_batch: 0.0 the loss is: 0.123626426 time for this batch: 0.737 -----------------a batch ends--------------- i_batch: 10.0 the loss is: 0.13921532 time for this batch: 0.734 -----------------a batch ends--------------- i_batch: 20.0 the loss is: 0.14113581 time for this batch: 0.653 -----------------a batch ends--------------- i_batch: 30.0 the loss is: 0.15941031 time for this batch: 0.821 -----------------a batch ends--------------- i_batch: 40.0 the loss is: 0.1503382 time for this batch: 1.025 -----------------a batch ends--------------- i_batch: 50.0 the loss is: 0.15162799 time for this batch: 0.746 -----------------a batch ends--------------- i_batch: 60.0 the loss is: 0.15870678 time for this batch: 0.77 -----------------a batch ends--------------- train loss for this epoch: 0.141576
----------------validate------------------- ave Recall 0.6722575385003878 ave NDCG 0.5673885876380342 ----------------test------------------- ave Recall 0.6553174846964686 ave NDCG 0.5446262199505156
running time for this epoch: 52.00571918487549 running time until now: 1802.3381140232086 -------------------------an epoch ends --------------------------- i_epoch: 32 ----------------an epoch starts------------------- # batch: 63 i_batch: 0.0 the loss is: 0.14397788 time for this batch: 0.702 -----------------a batch ends--------------- i_batch: 10.0 the loss is: 0.1339129 time for this batch: 0.685 -----------------a batch ends--------------- i_batch: 20.0 the loss is: 0.14422213 time for this batch: 0.747 -----------------a batch ends--------------- i_batch: 30.0 the loss is: 0.13902041 time for this batch: 0.684 -----------------a batch ends--------------- i_batch: 40.0 the loss is: 0.15156305 time for this batch: 0.752 -----------------a batch ends--------------- i_batch: 50.0 the loss is: 0.13264874 time for this batch: 0.708 -----------------a batch ends--------------- i_batch: 60.0 the loss is: 0.14247462 time for this batch: 0.678 -----------------a batch ends--------------- train loss for this epoch: 0.142054
----------------validate------------------- ave Recall 0.672941817786917 ave NDCG 0.5721138355496171 ----------------test------------------- ave Recall 0.6624535822642746 ave NDCG 0.5537501326638341
running time for this epoch: 49.760125398635864 running time until now: 1852.0983164310455 -------------------------an epoch ends --------------------------- i_epoch: 33 ----------------an epoch starts------------------- # batch: 63 i_batch: 0.0 the loss is: 0.13392112 time for this batch: 0.812 -----------------a batch ends--------------- i_batch: 10.0 the loss is: 0.13663408 time for this batch: 0.793 -----------------a batch ends--------------- i_batch: 20.0 the loss is: 0.15225321 time for this batch: 0.855 -----------------a batch ends--------------- i_batch: 30.0 the loss is: 0.132799 time for this batch: 0.594 -----------------a batch ends--------------- i_batch: 40.0 the loss is: 0.13766326 time for this batch: 0.886 -----------------a batch ends--------------- i_batch: 50.0 the loss is: 0.14672768 time for this batch: 0.813 -----------------a batch ends--------------- i_batch: 60.0 the loss is: 0.14056462 time for this batch: 0.627 -----------------a batch ends--------------- train loss for this epoch: 0.141399
----------------validate------------------- ave Recall 0.6692470074913787 ave NDCG 0.5645445678537072 ----------------test------------------- ave Recall 0.6529929404921752 ave NDCG 0.5462208550326141
running time for this epoch: 50.27941846847534 running time until now: 1902.3777947425842 -------------------------an epoch ends --------------------------- i_epoch: 34 ----------------an epoch starts------------------- # batch: 63 i_batch: 0.0 the loss is: 0.14265929 time for this batch: 0.752 -----------------a batch ends--------------- i_batch: 10.0 the loss is: 0.14688732 time for this batch: 0.644 -----------------a batch ends--------------- i_batch: 20.0 the loss is: 0.13841371 time for this batch: 0.666 -----------------a batch ends--------------- i_batch: 30.0 the loss is: 0.14645328 time for this batch: 0.742 -----------------a batch ends--------------- i_batch: 40.0 the loss is: 0.1544339 time for this batch: 0.825 -----------------a batch ends--------------- i_batch: 50.0 the loss is: 0.14307845 time for this batch: 0.922 -----------------a batch ends--------------- i_batch: 60.0 the loss is: 0.14397702 time for this batch: 0.876 -----------------a batch ends--------------- train loss for this epoch: 0.140961
----------------validate------------------- ave Recall 0.6691969933240303 ave NDCG 0.565837648670329 ----------------test------------------- ave Recall 0.6623868610501877 ave NDCG 0.5544691295598819
running time for this epoch: 54.3826744556427 running time until now: 1956.760513305664 -------------------------an epoch ends --------------------------- i_epoch: 35 ----------------an epoch starts------------------- # batch: 63 i_batch: 0.0 the loss is: 0.13612689 time for this batch: 0.655 -----------------a batch ends--------------- i_batch: 10.0 the loss is: 0.13766019 time for this batch: 0.657 -----------------a batch ends--------------- i_batch: 20.0 the loss is: 0.13739687 time for this batch: 0.762 -----------------a batch ends--------------- i_batch: 30.0 the loss is: 0.10762192 time for this batch: 0.612 -----------------a batch ends--------------- i_batch: 40.0 the loss is: 0.13358015 time for this batch: 0.717 -----------------a batch ends--------------- i_batch: 50.0 the loss is: 0.13942927 time for this batch: 0.646 -----------------a batch ends--------------- i_batch: 60.0 the loss is: 0.14700495 time for this batch: 0.626 -----------------a batch ends--------------- train loss for this epoch: 0.139817
----------------validate------------------- ave Recall 0.6701055927921666 ave NDCG 0.5676777674780583 ----------------test------------------- ave Recall 0.6592349789387273 ave NDCG 0.5502452284965225
running time for this epoch: 45.172913789749146 running time until now: 2001.9335329532623 -------------------------an epoch ends --------------------------- i_epoch: 36 ----------------an epoch starts------------------- # batch: 63 i_batch: 0.0 the loss is: 0.14123252 time for this batch: 0.581 -----------------a batch ends--------------- i_batch: 10.0 the loss is: 0.13919634 time for this batch: 0.606 -----------------a batch ends--------------- i_batch: 20.0 the loss is: 0.1427258 time for this batch: 0.58 -----------------a batch ends--------------- i_batch: 30.0 the loss is: 0.12651744 time for this batch: 0.682 -----------------a batch ends--------------- i_batch: 40.0 the loss is: 0.14034876 time for this batch: 0.662 -----------------a batch ends--------------- i_batch: 50.0 the loss is: 0.14243889 time for this batch: 0.606 -----------------a batch ends--------------- i_batch: 60.0 the loss is: 0.137736 time for this batch: 0.589 -----------------a batch ends--------------- train loss for this epoch: 0.141179
----------------validate------------------- ave Recall 0.6648144569602208 ave NDCG 0.5645268936094441 ----------------test------------------- ave Recall 0.6603103384982554 ave NDCG 0.5491759656506919
running time for this epoch: 44.98262000083923 running time until now: 2046.916222333908 -------------------------an epoch ends --------------------------- i_epoch: 37 ----------------an epoch starts------------------- # batch: 63 i_batch: 0.0 the loss is: 0.13578638 time for this batch: 0.569 -----------------a batch ends--------------- i_batch: 10.0 the loss is: 0.13459414 time for this batch: 0.574 -----------------a batch ends--------------- i_batch: 20.0 the loss is: 0.13164148 time for this batch: 0.618 -----------------a batch ends--------------- i_batch: 30.0 the loss is: 0.15062937 time for this batch: 0.659 -----------------a batch ends--------------- i_batch: 40.0 the loss is: 0.143253 time for this batch: 0.736 -----------------a batch ends--------------- i_batch: 50.0 the loss is: 0.15114138 time for this batch: 0.653 -----------------a batch ends--------------- i_batch: 60.0 the loss is: 0.13428396 time for this batch: 0.626 -----------------a batch ends--------------- train loss for this epoch: 0.139467
----------------validate------------------- ave Recall 0.6636418030053968 ave NDCG 0.5625760598721443 ----------------test------------------- ave Recall 0.6567062037031755 ave NDCG 0.5495102108012694
running time for this epoch: 44.06864380836487 running time until now: 2090.9849066734314 -------------------------an epoch ends --------------------------- i_epoch: 38 ----------------an epoch starts------------------- # batch: 63 i_batch: 0.0 the loss is: 0.11557686 time for this batch: 0.613 -----------------a batch ends--------------- i_batch: 10.0 the loss is: 0.14098814 time for this batch: 0.647 -----------------a batch ends--------------- i_batch: 20.0 the loss is: 0.1446417 time for this batch: 0.613 -----------------a batch ends--------------- i_batch: 30.0 the loss is: 0.1408126 time for this batch: 0.584 -----------------a batch ends--------------- i_batch: 40.0 the loss is: 0.14281458 time for this batch: 0.65 -----------------a batch ends--------------- i_batch: 50.0 the loss is: 0.16148569 time for this batch: 0.651 -----------------a batch ends--------------- i_batch: 60.0 the loss is: 0.14226165 time for this batch: 0.638 -----------------a batch ends--------------- train loss for this epoch: 0.138753
----------------validate------------------- ave Recall 0.6701774146578328 ave NDCG 0.5668760874378678 ----------------test------------------- ave Recall 0.6622800518786164 ave NDCG 0.5522893658492317
running time for this epoch: 44.56523251533508 running time until now: 2135.5502033233643 -------------------------an epoch ends --------------------------- i_epoch: 39 ----------------an epoch starts------------------- # batch: 63 i_batch: 0.0 the loss is: 0.13176706 time for this batch: 0.665 -----------------a batch ends--------------- i_batch: 10.0 the loss is: 0.12549706 time for this batch: 0.692 -----------------a batch ends--------------- i_batch: 20.0 the loss is: 0.1314267 time for this batch: 0.699 -----------------a batch ends--------------- i_batch: 30.0 the loss is: 0.14059675 time for this batch: 0.647 -----------------a batch ends--------------- i_batch: 40.0 the loss is: 0.13170731 time for this batch: 0.628 -----------------a batch ends--------------- i_batch: 50.0 the loss is: 0.15132067 time for this batch: 0.703 -----------------a batch ends--------------- i_batch: 60.0 the loss is: 0.12542741 time for this batch: 0.65 -----------------a batch ends--------------- train loss for this epoch: 0.13906
----------------validate------------------- ave Recall 0.6664719281962783 ave NDCG 0.5674759974516995 ----------------test------------------- ave Recall 0.6576343321913741 ave NDCG 0.5489996841771528
running time for this epoch: 46.08642268180847 running time until now: 2181.6367263793945 -------------------------an epoch ends --------------------------- i_epoch: 40 ----------------an epoch starts------------------- # batch: 63 i_batch: 0.0 the loss is: 0.122823715 time for this batch: 0.747 -----------------a batch ends--------------- i_batch: 10.0 the loss is: 0.12501101 time for this batch: 0.724 -----------------a batch ends--------------- i_batch: 20.0 the loss is: 0.13248357 time for this batch: 0.737 -----------------a batch ends--------------- i_batch: 30.0 the loss is: 0.13866705 time for this batch: 0.701 -----------------a batch ends--------------- i_batch: 40.0 the loss is: 0.13504085 time for this batch: 0.569 -----------------a batch ends--------------- i_batch: 50.0 the loss is: 0.13733456 time for this batch: 0.696 -----------------a batch ends--------------- i_batch: 60.0 the loss is: 0.14797288 time for this batch: 0.709 -----------------a batch ends--------------- train loss for this epoch: 0.13886
----------------validate------------------- ave Recall 0.6680740766801878 ave NDCG 0.5675610058107569 ----------------test------------------- ave Recall 0.6597769629028298 ave NDCG 0.5515143583851834
running time for this epoch: 46.72116446495056 running time until now: 2228.3579416275024 -------------------------an epoch ends --------------------------- i_epoch: 41 ----------------an epoch starts------------------- # batch: 63 i_batch: 0.0 the loss is: 0.12768906 time for this batch: 0.542 -----------------a batch ends--------------- i_batch: 10.0 the loss is: 0.14262351 time for this batch: 0.657 -----------------a batch ends--------------- i_batch: 20.0 the loss is: 0.13413423 time for this batch: 0.613 -----------------a batch ends--------------- i_batch: 30.0 the loss is: 0.1474539 time for this batch: 0.699 -----------------a batch ends--------------- i_batch: 40.0 the loss is: 0.13238269 time for this batch: 0.553 -----------------a batch ends--------------- i_batch: 50.0 the loss is: 0.14182132 time for this batch: 0.665 -----------------a batch ends--------------- i_batch: 60.0 the loss is: 0.13720334 time for this batch: 0.647 -----------------a batch ends--------------- train loss for this epoch: 0.137589
----------------validate------------------- ave Recall 0.6672130298414379 ave NDCG 0.5664064323255937 ----------------test------------------- ave Recall 0.6534532421480362 ave NDCG 0.5495934796188758
running time for this epoch: 44.99138855934143 running time until now: 2273.349418401718 -------------------------an epoch ends --------------------------- i_epoch: 42 ----------------an epoch starts------------------- # batch: 63 i_batch: 0.0 the loss is: 0.12870733 time for this batch: 0.626 -----------------a batch ends--------------- i_batch: 10.0 the loss is: 0.12638284 time for this batch: 0.563 -----------------a batch ends--------------- i_batch: 20.0 the loss is: 0.14208354 time for this batch: 0.813 -----------------a batch ends--------------- i_batch: 30.0 the loss is: 0.12797447 time for this batch: 0.61 -----------------a batch ends--------------- i_batch: 40.0 the loss is: 0.1629552 time for this batch: 0.711 -----------------a batch ends--------------- i_batch: 50.0 the loss is: 0.13960592 time for this batch: 0.664 -----------------a batch ends--------------- i_batch: 60.0 the loss is: 0.15463471 time for this batch: 0.658 -----------------a batch ends--------------- train loss for this epoch: 0.137578
----------------validate------------------- ave Recall 0.6727698013522961 ave NDCG 0.5709486081091311 ----------------test------------------- ave Recall 0.6626148457674916 ave NDCG 0.5560698246181607
running time for this epoch: 43.98703169822693 running time until now: 2317.3365256786346 -------------------------an epoch ends --------------------------- i_epoch: 43 ----------------an epoch starts------------------- # batch: 63 i_batch: 0.0 the loss is: 0.13446192 time for this batch: 0.553 -----------------a batch ends--------------- i_batch: 10.0 the loss is: 0.14215711 time for this batch: 0.62 -----------------a batch ends--------------- i_batch: 20.0 the loss is: 0.12131637 time for this batch: 0.567 -----------------a batch ends--------------- i_batch: 30.0 the loss is: 0.1380943 time for this batch: 0.583 -----------------a batch ends--------------- i_batch: 40.0 the loss is: 0.13817298 time for this batch: 0.667 -----------------a batch ends--------------- i_batch: 50.0 the loss is: 0.12947164 time for this batch: 0.74 -----------------a batch ends--------------- i_batch: 60.0 the loss is: 0.13767128 time for this batch: 0.646 -----------------a batch ends--------------- train loss for this epoch: 0.136525
----------------validate------------------- ave Recall 0.6724146626513193 ave NDCG 0.5725381653184812 ----------------test------------------- ave Recall 0.6682552232232336 ave NDCG 0.5612470422623492
running time for this epoch: 43.3808012008667 running time until now: 2360.7173869609833 -------------------------an epoch ends --------------------------- i_epoch: 44 ----------------an epoch starts------------------- # batch: 63 i_batch: 0.0 the loss is: 0.11994261 time for this batch: 0.614 -----------------a batch ends--------------- i_batch: 10.0 the loss is: 0.13571706 time for this batch: 0.686 -----------------a batch ends--------------- i_batch: 20.0 the loss is: 0.1358186 time for this batch: 0.618 -----------------a batch ends--------------- i_batch: 30.0 the loss is: 0.13514915 time for this batch: 0.56 -----------------a batch ends--------------- i_batch: 40.0 the loss is: 0.13354859 time for this batch: 0.591 -----------------a batch ends--------------- i_batch: 50.0 the loss is: 0.15637895 time for this batch: 0.752 -----------------a batch ends--------------- i_batch: 60.0 the loss is: 0.13644725 time for this batch: 0.607 -----------------a batch ends--------------- train loss for this epoch: 0.136326
----------------validate------------------- ave Recall 0.6723281595817545 ave NDCG 0.5689081931073179 ----------------test------------------- ave Recall 0.661693551192811 ave NDCG 0.5552231975467637
running time for this epoch: 43.502023220062256 running time until now: 2404.2194509506226 -------------------------an epoch ends --------------------------- i_epoch: 45 ----------------an epoch starts------------------- # batch: 63 i_batch: 0.0 the loss is: 0.13171388 time for this batch: 0.621 -----------------a batch ends--------------- i_batch: 10.0 the loss is: 0.13059786 time for this batch: 0.491 -----------------a batch ends--------------- i_batch: 20.0 the loss is: 0.12295322 time for this batch: 0.566 -----------------a batch ends--------------- i_batch: 30.0 the loss is: 0.16085574 time for this batch: 0.58 -----------------a batch ends--------------- i_batch: 40.0 the loss is: 0.13743426 time for this batch: 0.561 -----------------a batch ends--------------- i_batch: 50.0 the loss is: 0.13194972 time for this batch: 0.652 -----------------a batch ends--------------- i_batch: 60.0 the loss is: 0.13942605 time for this batch: 0.615 -----------------a batch ends--------------- train loss for this epoch: 0.136666
----------------validate------------------- ave Recall 0.6731312072851539 ave NDCG 0.5725293499382256 ----------------test------------------- ave Recall 0.6651521031803808 ave NDCG 0.5580960161144373
running time for this epoch: 40.72740983963013 running time until now: 2444.9469175338745 -------------------------an epoch ends --------------------------- i_epoch: 46 ----------------an epoch starts------------------- # batch: 63 i_batch: 0.0 the loss is: 0.1365901 time for this batch: 0.628 -----------------a batch ends--------------- i_batch: 10.0 the loss is: 0.13741788 time for this batch: 0.478 -----------------a batch ends--------------- i_batch: 20.0 the loss is: 0.13482618 time for this batch: 0.651 -----------------a batch ends--------------- i_batch: 30.0 the loss is: 0.14465387 time for this batch: 0.598 -----------------a batch ends--------------- i_batch: 40.0 the loss is: 0.14623216 time for this batch: 0.599 -----------------a batch ends--------------- i_batch: 50.0 the loss is: 0.14186954 time for this batch: 0.514 -----------------a batch ends--------------- i_batch: 60.0 the loss is: 0.15106136 time for this batch: 0.654 -----------------a batch ends--------------- train loss for this epoch: 0.136697
----------------validate------------------- ave Recall 0.670383923659115 ave NDCG 0.5676558999034157 ----------------test------------------- ave Recall 0.6593029285106621 ave NDCG 0.549848719172909
running time for this epoch: 41.40817070007324 running time until now: 2486.355129003525 -------------------------an epoch ends --------------------------- i_epoch: 47 ----------------an epoch starts------------------- # batch: 63 i_batch: 0.0 the loss is: 0.13942671 time for this batch: 0.63 -----------------a batch ends--------------- i_batch: 10.0 the loss is: 0.14002356 time for this batch: 0.516 -----------------a batch ends--------------- i_batch: 20.0 the loss is: 0.14855799 time for this batch: 0.568 -----------------a batch ends--------------- i_batch: 30.0 the loss is: 0.14118499 time for this batch: 0.634 -----------------a batch ends--------------- i_batch: 40.0 the loss is: 0.14180753 time for this batch: 0.594 -----------------a batch ends--------------- i_batch: 50.0 the loss is: 0.13712227 time for this batch: 0.618 -----------------a batch ends--------------- i_batch: 60.0 the loss is: 0.14097244 time for this batch: 0.532 -----------------a batch ends--------------- train loss for this epoch: 0.137024
----------------validate------------------- ave Recall 0.6673075126830769 ave NDCG 0.5656718025318557 ----------------test------------------- ave Recall 0.6638256064393327 ave NDCG 0.5536749331551168
running time for this epoch: 40.942848920822144 running time until now: 2527.2980654239655 -------------------------an epoch ends --------------------------- i_epoch: 48 ----------------an epoch starts------------------- # batch: 63 i_batch: 0.0 the loss is: 0.15149954 time for this batch: 0.498 -----------------a batch ends--------------- i_batch: 10.0 the loss is: 0.12899332 time for this batch: 0.486 -----------------a batch ends--------------- i_batch: 20.0 the loss is: 0.1513854 time for this batch: 0.575 -----------------a batch ends--------------- i_batch: 30.0 the loss is: 0.13876398 time for this batch: 0.478 -----------------a batch ends--------------- i_batch: 40.0 the loss is: 0.1370689 time for this batch: 0.668 -----------------a batch ends--------------- i_batch: 50.0 the loss is: 0.12992525 time for this batch: 0.591 -----------------a batch ends--------------- i_batch: 60.0 the loss is: 0.14444086 time for this batch: 0.594 -----------------a batch ends--------------- train loss for this epoch: 0.136126
----------------validate------------------- ave Recall 0.6708891444781044 ave NDCG 0.5655976397667541 ----------------test------------------- ave Recall 0.6592129360065506 ave NDCG 0.5499077288114314
running time for this epoch: 39.05191993713379 running time until now: 2566.35005569458 -------------------------an epoch ends --------------------------- i_epoch: 49 ----------------an epoch starts------------------- # batch: 63 i_batch: 0.0 the loss is: 0.12144025 time for this batch: 0.529 -----------------a batch ends--------------- i_batch: 10.0 the loss is: 0.1437082 time for this batch: 0.611 -----------------a batch ends--------------- i_batch: 20.0 the loss is: 0.14582443 time for this batch: 0.613 -----------------a batch ends--------------- i_batch: 30.0 the loss is: 0.13719304 time for this batch: 0.591 -----------------a batch ends--------------- i_batch: 40.0 the loss is: 0.1347489 time for this batch: 0.633 -----------------a batch ends--------------- i_batch: 50.0 the loss is: 0.13520697 time for this batch: 0.572 -----------------a batch ends--------------- i_batch: 60.0 the loss is: 0.13494672 time for this batch: 0.571 -----------------a batch ends--------------- train loss for this epoch: 0.135016
----------------validate------------------- ave Recall 0.6715515249551189 ave NDCG 0.5694834227172593 ----------------test------------------- ave Recall 0.6609424407551086 ave NDCG 0.5549364069034587
running time for this epoch: 40.962045669555664 running time until now: 2607.3121938705444 -------------------------an epoch ends --------------------------- i_epoch: 50 ----------------an epoch starts------------------- # batch: 63 i_batch: 0.0 the loss is: 0.14696412 time for this batch: 0.553 -----------------a batch ends--------------- i_batch: 10.0 the loss is: 0.13081051 time for this batch: 0.585 -----------------a batch ends--------------- i_batch: 20.0 the loss is: 0.12709083 time for this batch: 0.592 -----------------a batch ends--------------- i_batch: 30.0 the loss is: 0.13231604 time for this batch: 0.614 -----------------a batch ends--------------- i_batch: 40.0 the loss is: 0.13441089 time for this batch: 0.585 -----------------a batch ends--------------- i_batch: 50.0 the loss is: 0.14059773 time for this batch: 0.564 -----------------a batch ends--------------- i_batch: 60.0 the loss is: 0.14278321 time for this batch: 0.524 -----------------a batch ends--------------- train loss for this epoch: 0.135309
----------------validate------------------- ave Recall 0.6754839494207725 ave NDCG 0.5687233026023568 ----------------test------------------- ave Recall 0.6672498640171579 ave NDCG 0.5604292372188545
running time for this epoch: 42.330549478530884 running time until now: 2649.642879486084 -------------------------an epoch ends --------------------------- i_epoch: 51 ----------------an epoch starts------------------- # batch: 63 i_batch: 0.0 the loss is: 0.12291955 time for this batch: 0.527 -----------------a batch ends--------------- i_batch: 10.0 the loss is: 0.13226257 time for this batch: 0.615 -----------------a batch ends--------------- i_batch: 20.0 the loss is: 0.12780222 time for this batch: 0.603 -----------------a batch ends--------------- i_batch: 30.0 the loss is: 0.14536488 time for this batch: 0.587 -----------------a batch ends--------------- i_batch: 40.0 the loss is: 0.14745209 time for this batch: 0.693 -----------------a batch ends--------------- i_batch: 50.0 the loss is: 0.14574224 time for this batch: 0.643 -----------------a batch ends--------------- i_batch: 60.0 the loss is: 0.15427542 time for this batch: 0.579 -----------------a batch ends--------------- train loss for this epoch: 0.13609
----------------validate------------------- ave Recall 0.6740952231779698 ave NDCG 0.5661803416182064 ----------------test------------------- ave Recall 0.6606425634110347 ave NDCG 0.5517984093743032
running time for this epoch: 44.69580578804016 running time until now: 2694.3387818336487 -------------------------an epoch ends --------------------------- i_epoch: 52 ----------------an epoch starts------------------- # batch: 63 i_batch: 0.0 the loss is: 0.11862414 time for this batch: 0.552 -----------------a batch ends--------------- i_batch: 10.0 the loss is: 0.1402171 time for this batch: 0.592 -----------------a batch ends--------------- i_batch: 20.0 the loss is: 0.12325546 time for this batch: 0.656 -----------------a batch ends--------------- i_batch: 30.0 the loss is: 0.14117965 time for this batch: 0.608 -----------------a batch ends--------------- i_batch: 40.0 the loss is: 0.13427924 time for this batch: 0.644 -----------------a batch ends--------------- i_batch: 50.0 the loss is: 0.14321998 time for this batch: 0.619 -----------------a batch ends--------------- i_batch: 60.0 the loss is: 0.13860805 time for this batch: 0.584 -----------------a batch ends--------------- train loss for this epoch: 0.135227
----------------validate------------------- ave Recall 0.6723247435286628 ave NDCG 0.5659721240671791 ----------------test------------------- ave Recall 0.6608948530533951 ave NDCG 0.5489118448992015
running time for this epoch: 42.36934423446655 running time until now: 2736.7081797122955 -------------------------an epoch ends --------------------------- i_epoch: 53 ----------------an epoch starts------------------- # batch: 63 i_batch: 0.0 the loss is: 0.14687702 time for this batch: 0.548 -----------------a batch ends--------------- i_batch: 10.0 the loss is: 0.12633064 time for this batch: 0.573 -----------------a batch ends--------------- i_batch: 20.0 the loss is: 0.12040923 time for this batch: 0.604 -----------------a batch ends--------------- i_batch: 30.0 the loss is: 0.12721369 time for this batch: 0.65 -----------------a batch ends--------------- i_batch: 40.0 the loss is: 0.13841099 time for this batch: 0.64 -----------------a batch ends--------------- i_batch: 50.0 the loss is: 0.14283794 time for this batch: 0.575 -----------------a batch ends--------------- i_batch: 60.0 the loss is: 0.13967699 time for this batch: 0.585 -----------------a batch ends--------------- train loss for this epoch: 0.133322
----------------validate------------------- ave Recall 0.6736377791786732 ave NDCG 0.5660888899414201 ----------------test------------------- ave Recall 0.6570137602354799 ave NDCG 0.548059371238735
running time for this epoch: 41.581591844558716 running time until now: 2778.2898688316345 -------------------------an epoch ends --------------------------- i_epoch: 54 ----------------an epoch starts------------------- # batch: 63 i_batch: 0.0 the loss is: 0.12903045 time for this batch: 0.553 -----------------a batch ends--------------- i_batch: 10.0 the loss is: 0.13389927 time for this batch: 0.564 -----------------a batch ends--------------- i_batch: 20.0 the loss is: 0.12958437 time for this batch: 0.579 -----------------a batch ends--------------- i_batch: 30.0 the loss is: 0.15084136 time for this batch: 0.578 -----------------a batch ends--------------- i_batch: 40.0 the loss is: 0.13473816 time for this batch: 0.582 -----------------a batch ends--------------- i_batch: 50.0 the loss is: 0.13719046 time for this batch: 0.589 -----------------a batch ends--------------- i_batch: 60.0 the loss is: 0.1327137 time for this batch: 0.623 -----------------a batch ends--------------- train loss for this epoch: 0.134824
----------------validate------------------- ave Recall 0.6693126781879227 ave NDCG 0.5665139926776868 ----------------test------------------- ave Recall 0.6574142328157015 ave NDCG 0.5481115504885931
running time for this epoch: 41.44312334060669 running time until now: 2819.7330679893494 -------------------------an epoch ends --------------------------- i_epoch: 55 ----------------an epoch starts------------------- # batch: 63 i_batch: 0.0 the loss is: 0.12198973 time for this batch: 0.522 -----------------a batch ends--------------- i_batch: 10.0 the loss is: 0.12507361 time for this batch: 0.637 -----------------a batch ends--------------- i_batch: 20.0 the loss is: 0.13447425 time for this batch: 0.634 -----------------a batch ends--------------- i_batch: 30.0 the loss is: 0.13210286 time for this batch: 0.587 -----------------a batch ends--------------- i_batch: 40.0 the loss is: 0.1318819 time for this batch: 0.775 -----------------a batch ends--------------- i_batch: 50.0 the loss is: 0.12742785 time for this batch: 0.758 -----------------a batch ends--------------- i_batch: 60.0 the loss is: 0.1318487 time for this batch: 0.734 -----------------a batch ends--------------- train loss for this epoch: 0.134226
----------------validate------------------- ave Recall 0.6638743445714366 ave NDCG 0.5639154263757014 ----------------test------------------- ave Recall 0.6540237266274778 ave NDCG 0.5480778708227143
running time for this epoch: 45.50716161727905 running time until now: 2865.2402811050415 -------------------------an epoch ends --------------------------- i_epoch: 56 ----------------an epoch starts------------------- # batch: 63 i_batch: 0.0 the loss is: 0.13511698 time for this batch: 0.698 -----------------a batch ends--------------- i_batch: 10.0 the loss is: 0.13123998 time for this batch: 0.762 -----------------a batch ends--------------- i_batch: 20.0 the loss is: 0.12715408 time for this batch: 0.729 -----------------a batch ends--------------- i_batch: 30.0 the loss is: 0.12570024 time for this batch: 0.626 -----------------a batch ends--------------- i_batch: 40.0 the loss is: 0.12925221 time for this batch: 0.629 -----------------a batch ends--------------- i_batch: 50.0 the loss is: 0.13351373 time for this batch: 0.805 -----------------a batch ends--------------- i_batch: 60.0 the loss is: 0.13923815 time for this batch: 0.745 -----------------a batch ends--------------- train loss for this epoch: 0.133846
----------------validate------------------- ave Recall 0.6692652910422199 ave NDCG 0.5671945913932063 ----------------test------------------- ave Recall 0.6567004332110731 ave NDCG 0.5492664602856597
running time for this epoch: 48.20149278640747 running time until now: 2913.4418499469757 -------------------------an epoch ends --------------------------- i_epoch: 57 ----------------an epoch starts------------------- # batch: 63 i_batch: 0.0 the loss is: 0.1270817 time for this batch: 0.701 -----------------a batch ends--------------- i_batch: 10.0 the loss is: 0.13031527 time for this batch: 0.535 -----------------a batch ends--------------- i_batch: 20.0 the loss is: 0.14615822 time for this batch: 0.638 -----------------a batch ends--------------- i_batch: 30.0 the loss is: 0.1446943 time for this batch: 0.573 -----------------a batch ends--------------- i_batch: 40.0 the loss is: 0.13821009 time for this batch: 0.604 -----------------a batch ends--------------- i_batch: 50.0 the loss is: 0.13085061 time for this batch: 0.583 -----------------a batch ends--------------- i_batch: 60.0 the loss is: 0.13273197 time for this batch: 0.569 -----------------a batch ends--------------- train loss for this epoch: 0.135139
----------------validate------------------- ave Recall 0.672151514397165 ave NDCG 0.5681729492961425 ----------------test------------------- ave Recall 0.6597052889890709 ave NDCG 0.54796959335271
running time for this epoch: 42.06080150604248 running time until now: 2955.5027034282684 -------------------------an epoch ends --------------------------- i_epoch: 58 ----------------an epoch starts------------------- # batch: 63 i_batch: 0.0 the loss is: 0.13818243 time for this batch: 0.535 -----------------a batch ends--------------- i_batch: 10.0 the loss is: 0.13534124 time for this batch: 0.634 -----------------a batch ends--------------- i_batch: 20.0 the loss is: 0.11806026 time for this batch: 0.551 -----------------a batch ends--------------- i_batch: 30.0 the loss is: 0.141565 time for this batch: 0.617 -----------------a batch ends--------------- i_batch: 40.0 the loss is: 0.13467482 time for this batch: 0.602 -----------------a batch ends--------------- i_batch: 50.0 the loss is: 0.1332196 time for this batch: 0.61 -----------------a batch ends--------------- i_batch: 60.0 the loss is: 0.1324912 time for this batch: 0.628 -----------------a batch ends--------------- train loss for this epoch: 0.133933
----------------validate------------------- ave Recall 0.6665930564401834 ave NDCG 0.5637938861809845 ----------------test------------------- ave Recall 0.6559497409010283 ave NDCG 0.5463337391955574
running time for this epoch: 41.436739683151245 running time until now: 2996.9395525455475 -------------------------an epoch ends --------------------------- i_epoch: 59 ----------------an epoch starts------------------- # batch: 63 i_batch: 0.0 the loss is: 0.11662425 time for this batch: 0.546 -----------------a batch ends--------------- i_batch: 10.0 the loss is: 0.13532124 time for this batch: 0.596 -----------------a batch ends--------------- i_batch: 20.0 the loss is: 0.15339954 time for this batch: 0.567 -----------------a batch ends--------------- i_batch: 30.0 the loss is: 0.15091136 time for this batch: 0.584 -----------------a batch ends--------------- i_batch: 40.0 the loss is: 0.12799136 time for this batch: 0.546 -----------------a batch ends--------------- i_batch: 50.0 the loss is: 0.12799022 time for this batch: 0.594 -----------------a batch ends--------------- i_batch: 60.0 the loss is: 0.14294213 time for this batch: 0.553 -----------------a batch ends--------------- train loss for this epoch: 0.133963
----------------validate------------------- ave Recall 0.6693842824613684 ave NDCG 0.5638121089631642 ----------------test------------------- ave Recall 0.6619028144195311 ave NDCG 0.551423831683687
running time for this epoch: 40.93689274787903 running time until now: 3037.8765263557434 -------------------------an epoch ends --------------------------- i_epoch: 60 ----------------an epoch starts------------------- # batch: 63 i_batch: 0.0 the loss is: 0.13985255 time for this batch: 0.507 -----------------a batch ends--------------- i_batch: 10.0 the loss is: 0.13930416 time for this batch: 0.611 -----------------a batch ends--------------- i_batch: 20.0 the loss is: 0.12792815 time for this batch: 0.616 -----------------a batch ends--------------- i_batch: 30.0 the loss is: 0.1405336 time for this batch: 0.66 -----------------a batch ends--------------- i_batch: 40.0 the loss is: 0.14334613 time for this batch: 0.619 -----------------a batch ends--------------- i_batch: 50.0 the loss is: 0.13071397 time for this batch: 0.619 -----------------a batch ends--------------- i_batch: 60.0 the loss is: 0.13438961 time for this batch: 0.611 -----------------a batch ends--------------- train loss for this epoch: 0.134072
----------------validate------------------- ave Recall 0.6672201288177069 ave NDCG 0.5654784911184513 ----------------test------------------- ave Recall 0.6617562569859237 ave NDCG 0.5542115498684241
running time for this epoch: 41.323227643966675 running time until now: 3079.19984292984 -------------------------an epoch ends --------------------------- i_epoch: 61 ----------------an epoch starts------------------- # batch: 63 i_batch: 0.0 the loss is: 0.13473177 time for this batch: 0.558 -----------------a batch ends--------------- i_batch: 10.0 the loss is: 0.13895552 time for this batch: 0.63 -----------------a batch ends--------------- i_batch: 20.0 the loss is: 0.123398624 time for this batch: 0.569 -----------------a batch ends--------------- i_batch: 30.0 the loss is: 0.13388811 time for this batch: 0.557 -----------------a batch ends--------------- i_batch: 40.0 the loss is: 0.13034338 time for this batch: 0.63 -----------------a batch ends--------------- i_batch: 50.0 the loss is: 0.13523442 time for this batch: 0.593 -----------------a batch ends--------------- i_batch: 60.0 the loss is: 0.13498002 time for this batch: 0.606 -----------------a batch ends--------------- train loss for this epoch: 0.132571
----------------validate------------------- ave Recall 0.671581344550306 ave NDCG 0.5675245180437248 ----------------test------------------- ave Recall 0.6588489968273014 ave NDCG 0.5545751400315032
running time for this epoch: 41.2673397064209 running time until now: 3120.467225790024 -------------------------an epoch ends --------------------------- i_epoch: 62 ----------------an epoch starts------------------- # batch: 63 i_batch: 0.0 the loss is: 0.13486752 time for this batch: 0.565 -----------------a batch ends--------------- i_batch: 10.0 the loss is: 0.117840946 time for this batch: 0.613 -----------------a batch ends--------------- i_batch: 20.0 the loss is: 0.12507932 time for this batch: 0.596 -----------------a batch ends--------------- i_batch: 30.0 the loss is: 0.13084733 time for this batch: 0.603 -----------------a batch ends--------------- i_batch: 40.0 the loss is: 0.14219043 time for this batch: 0.601 -----------------a batch ends--------------- i_batch: 50.0 the loss is: 0.13319856 time for this batch: 0.597 -----------------a batch ends--------------- i_batch: 60.0 the loss is: 0.14644979 time for this batch: 0.596 -----------------a batch ends--------------- train loss for this epoch: 0.133158
----------------validate------------------- ave Recall 0.6639083533105844 ave NDCG 0.5613508340060559 ----------------test------------------- ave Recall 0.6591269679017753 ave NDCG 0.5511116775995581
running time for this epoch: 41.62515449523926 running time until now: 3162.092423439026 -------------------------an epoch ends --------------------------- i_epoch: 63 ----------------an epoch starts------------------- # batch: 63 i_batch: 0.0 the loss is: 0.121539906 time for this batch: 0.552 -----------------a batch ends--------------- i_batch: 10.0 the loss is: 0.1355544 time for this batch: 0.595 -----------------a batch ends--------------- i_batch: 20.0 the loss is: 0.12902734 time for this batch: 0.575 -----------------a batch ends--------------- i_batch: 30.0 the loss is: 0.13072772 time for this batch: 0.601 -----------------a batch ends--------------- i_batch: 40.0 the loss is: 0.13583143 time for this batch: 0.574 -----------------a batch ends--------------- i_batch: 50.0 the loss is: 0.14262146 time for this batch: 0.6 -----------------a batch ends--------------- i_batch: 60.0 the loss is: 0.15781334 time for this batch: 0.6 -----------------a batch ends--------------- train loss for this epoch: 0.133167
----------------validate------------------- ave Recall 0.6652124839062751 ave NDCG 0.5614430738847825 ----------------test------------------- ave Recall 0.6516048159081422 ave NDCG 0.546959669311535
running time for this epoch: 40.41459679603577 running time until now: 3202.5070621967316 -------------------------an epoch ends --------------------------- i_epoch: 64 ----------------an epoch starts------------------- # batch: 63 i_batch: 0.0 the loss is: 0.1524623 time for this batch: 0.574 -----------------a batch ends--------------- i_batch: 10.0 the loss is: 0.12945266 time for this batch: 0.599 -----------------a batch ends--------------- i_batch: 20.0 the loss is: 0.12223812 time for this batch: 0.581 -----------------a batch ends--------------- i_batch: 30.0 the loss is: 0.13261992 time for this batch: 0.638 -----------------a batch ends--------------- i_batch: 40.0 the loss is: 0.1395796 time for this batch: 0.608 -----------------a batch ends--------------- i_batch: 50.0 the loss is: 0.14086327 time for this batch: 0.617 -----------------a batch ends--------------- i_batch: 60.0 the loss is: 0.13661732 time for this batch: 0.565 -----------------a batch ends--------------- train loss for this epoch: 0.133245
----------------validate------------------- ave Recall 0.66398839300995 ave NDCG 0.5617207381843952 ----------------test------------------- ave Recall 0.6563213039633912 ave NDCG 0.5495107684636927
running time for this epoch: 40.99692249298096 running time until now: 3243.5040385723114 -------------------------an epoch ends --------------------------- i_epoch: 65 ----------------an epoch starts------------------- # batch: 63 i_batch: 0.0 the loss is: 0.13212597 time for this batch: 0.545 -----------------a batch ends--------------- i_batch: 10.0 the loss is: 0.12587105 time for this batch: 0.64 -----------------a batch ends--------------- i_batch: 20.0 the loss is: 0.10710281 time for this batch: 0.634 -----------------a batch ends--------------- i_batch: 30.0 the loss is: 0.13044685 time for this batch: 0.577 -----------------a batch ends--------------- i_batch: 40.0 the loss is: 0.1337158 time for this batch: 0.502 -----------------a batch ends--------------- i_batch: 50.0 the loss is: 0.14671502 time for this batch: 0.592 -----------------a batch ends--------------- i_batch: 60.0 the loss is: 0.14124359 time for this batch: 0.598 -----------------a batch ends--------------- train loss for this epoch: 0.133673
----------------validate------------------- ave Recall 0.6717713244739608 ave NDCG 0.5672555383751693 ----------------test------------------- ave Recall 0.6626766394094142 ave NDCG 0.5528146828431673
running time for this epoch: 40.74333715438843 running time until now: 3284.2474670410156 -------------------------an epoch ends --------------------------- i_epoch: 66 ----------------an epoch starts------------------- # batch: 63 i_batch: 0.0 the loss is: 0.13009338 time for this batch: 0.536 -----------------a batch ends--------------- i_batch: 10.0 the loss is: 0.13543938 time for this batch: 0.585 -----------------a batch ends--------------- i_batch: 20.0 the loss is: 0.12070784 time for this batch: 0.573 -----------------a batch ends--------------- i_batch: 30.0 the loss is: 0.15605307 time for this batch: 0.636 -----------------a batch ends--------------- i_batch: 40.0 the loss is: 0.13549283 time for this batch: 0.596 -----------------a batch ends--------------- i_batch: 50.0 the loss is: 0.14260045 time for this batch: 0.598 -----------------a batch ends--------------- i_batch: 60.0 the loss is: 0.13790125 time for this batch: 0.595 -----------------a batch ends--------------- train loss for this epoch: 0.13275
----------------validate------------------- ave Recall 0.672949381430763 ave NDCG 0.5680729490596725 ----------------test------------------- ave Recall 0.6584242391011224 ave NDCG 0.5485559137525862
running time for this epoch: 41.731393337249756 running time until now: 3325.9789316654205 -------------------------an epoch ends --------------------------- i_epoch: 67 ----------------an epoch starts------------------- # batch: 63 i_batch: 0.0 the loss is: 0.13895923 time for this batch: 0.529 -----------------a batch ends--------------- i_batch: 10.0 the loss is: 0.12606736 time for this batch: 0.593 -----------------a batch ends--------------- i_batch: 20.0 the loss is: 0.13286069 time for this batch: 0.689 -----------------a batch ends--------------- i_batch: 30.0 the loss is: 0.11492211 time for this batch: 0.588 -----------------a batch ends--------------- i_batch: 40.0 the loss is: 0.13169613 time for this batch: 0.607 -----------------a batch ends--------------- i_batch: 50.0 the loss is: 0.13844514 time for this batch: 0.587 -----------------a batch ends--------------- i_batch: 60.0 the loss is: 0.142771 time for this batch: 0.592 -----------------a batch ends--------------- train loss for this epoch: 0.132251
----------------validate------------------- ave Recall 0.6665226286779402 ave NDCG 0.5648902759404496 ----------------test------------------- ave Recall 0.6541647873871729 ave NDCG 0.5481370396870129
running time for this epoch: 41.45913028717041 running time until now: 3367.438150405884 -------------------------an epoch ends --------------------------- i_epoch: 68 ----------------an epoch starts------------------- # batch: 63 i_batch: 0.0 the loss is: 0.12543373 time for this batch: 0.546 -----------------a batch ends--------------- i_batch: 10.0 the loss is: 0.13501261 time for this batch: 0.58 -----------------a batch ends--------------- i_batch: 20.0 the loss is: 0.10877004 time for this batch: 0.618 -----------------a batch ends--------------- i_batch: 30.0 the loss is: 0.13023797 time for this batch: 0.62 -----------------a batch ends--------------- i_batch: 40.0 the loss is: 0.14624265 time for this batch: 0.538 -----------------a batch ends--------------- i_batch: 50.0 the loss is: 0.12720425 time for this batch: 0.604 -----------------a batch ends--------------- i_batch: 60.0 the loss is: 0.13533852 time for this batch: 0.634 -----------------a batch ends--------------- train loss for this epoch: 0.13208
----------------validate------------------- ave Recall 0.6651079178062149 ave NDCG 0.5634487180149542 ----------------test------------------- ave Recall 0.6582645708131027 ave NDCG 0.551669506313779
running time for this epoch: 40.31872367858887 running time until now: 3407.757003545761 -------------------------an epoch ends --------------------------- i_epoch: 69 ----------------an epoch starts------------------- # batch: 63 i_batch: 0.0 the loss is: 0.1291028 time for this batch: 0.548 -----------------a batch ends--------------- i_batch: 10.0 the loss is: 0.12832102 time for this batch: 0.596 -----------------a batch ends--------------- i_batch: 20.0 the loss is: 0.11896944 time for this batch: 0.62 -----------------a batch ends--------------- i_batch: 30.0 the loss is: 0.1262183 time for this batch: 0.627 -----------------a batch ends--------------- i_batch: 40.0 the loss is: 0.14098549 time for this batch: 0.5 -----------------a batch ends--------------- i_batch: 50.0 the loss is: 0.12417483 time for this batch: 0.481 -----------------a batch ends--------------- i_batch: 60.0 the loss is: 0.12778431 time for this batch: 0.577 -----------------a batch ends--------------- train loss for this epoch: 0.132343
----------------validate------------------- ave Recall 0.6616004972291759 ave NDCG 0.5593600906318443 ----------------test------------------- ave Recall 0.6574367507968019 ave NDCG 0.5461021003824171
running time for this epoch: 38.884825229644775 running time until now: 3446.6419451236725 -------------------------an epoch ends --------------------------- i_epoch: 70 ----------------an epoch starts------------------- # batch: 63 i_batch: 0.0 the loss is: 0.1320995 time for this batch: 0.479 -----------------a batch ends--------------- i_batch: 10.0 the loss is: 0.143137 time for this batch: 0.5 -----------------a batch ends--------------- i_batch: 20.0 the loss is: 0.12315819 time for this batch: 0.519 -----------------a batch ends--------------- i_batch: 30.0 the loss is: 0.1298701 time for this batch: 0.493 -----------------a batch ends--------------- i_batch: 40.0 the loss is: 0.13161545 time for this batch: 0.497 -----------------a batch ends--------------- i_batch: 50.0 the loss is: 0.13985471 time for this batch: 0.497 -----------------a batch ends--------------- i_batch: 60.0 the loss is: 0.13400315 time for this batch: 0.509 -----------------a batch ends--------------- train loss for this epoch: 0.132959
----------------validate------------------- ave Recall 0.6602517431176453 ave NDCG 0.5596458860748376 ----------------test------------------- ave Recall 0.6541554215131158 ave NDCG 0.5467592314064535
running time for this epoch: 34.9971981048584 running time until now: 3481.6392612457275 -------------------------an epoch ends --------------------------- i_epoch: 71 ----------------an epoch starts------------------- # batch: 63 i_batch: 0.0 the loss is: 0.13643062 time for this batch: 0.526 -----------------a batch ends--------------- i_batch: 10.0 the loss is: 0.12168047 time for this batch: 0.477 -----------------a batch ends--------------- i_batch: 20.0 the loss is: 0.14414507 time for this batch: 0.513 -----------------a batch ends--------------- i_batch: 30.0 the loss is: 0.12383988 time for this batch: 0.515 -----------------a batch ends--------------- i_batch: 40.0 the loss is: 0.13763179 time for this batch: 0.479 -----------------a batch ends--------------- i_batch: 50.0 the loss is: 0.1305691 time for this batch: 0.51 -----------------a batch ends--------------- i_batch: 60.0 the loss is: 0.12728697 time for this batch: 0.495 -----------------a batch ends--------------- train loss for this epoch: 0.131195
----------------validate------------------- ave Recall 0.6714272134137349 ave NDCG 0.5660173952534419 ----------------test------------------- ave Recall 0.6545141847014941 ave NDCG 0.546643187082683
running time for this epoch: 35.37409234046936 running time until now: 3517.013432264328 -------------------------an epoch ends --------------------------- i_epoch: 72 ----------------an epoch starts------------------- # batch: 63 i_batch: 0.0 the loss is: 0.12830126 time for this batch: 0.611 -----------------a batch ends--------------- i_batch: 10.0 the loss is: 0.12674586 time for this batch: 0.621 -----------------a batch ends--------------- i_batch: 20.0 the loss is: 0.13043341 time for this batch: 0.556 -----------------a batch ends--------------- i_batch: 30.0 the loss is: 0.12708528 time for this batch: 0.558 -----------------a batch ends--------------- i_batch: 40.0 the loss is: 0.121352926 time for this batch: 0.572 -----------------a batch ends--------------- i_batch: 50.0 the loss is: 0.13213067 time for this batch: 0.611 -----------------a batch ends--------------- i_batch: 60.0 the loss is: 0.15672982 time for this batch: 0.62 -----------------a batch ends--------------- train loss for this epoch: 0.131075
----------------validate------------------- ave Recall 0.6676538625839197 ave NDCG 0.5662752408850888 ----------------test------------------- ave Recall 0.6555612161633536 ave NDCG 0.5468255814385783
running time for this epoch: 41.28895688056946 running time until now: 3558.3024826049805 -------------------------an epoch ends --------------------------- i_epoch: 73 ----------------an epoch starts------------------- # batch: 63 i_batch: 0.0 the loss is: 0.117299214 time for this batch: 0.563 -----------------a batch ends--------------- i_batch: 10.0 the loss is: 0.126307 time for this batch: 0.597 -----------------a batch ends--------------- i_batch: 20.0 the loss is: 0.12914208 time for this batch: 0.593 -----------------a batch ends--------------- i_batch: 30.0 the loss is: 0.13963017 time for this batch: 0.577 -----------------a batch ends--------------- i_batch: 40.0 the loss is: 0.14559191 time for this batch: 0.571 -----------------a batch ends--------------- i_batch: 50.0 the loss is: 0.122718275 time for this batch: 0.609 -----------------a batch ends--------------- i_batch: 60.0 the loss is: 0.12834106 time for this batch: 0.739 -----------------a batch ends--------------- train loss for this epoch: 0.131628
----------------validate------------------- ave Recall 0.6660753764226778 ave NDCG 0.5659896751258124 ----------------test------------------- ave Recall 0.6564321925764329 ave NDCG 0.5473714082458201
running time for this epoch: 40.891708850860596 running time until now: 3599.1942570209503 -------------------------an epoch ends --------------------------- i_epoch: 74 ----------------an epoch starts------------------- # batch: 63 i_batch: 0.0 the loss is: 0.13763234 time for this batch: 0.563 -----------------a batch ends--------------- i_batch: 10.0 the loss is: 0.12062025 time for this batch: 0.717 -----------------a batch ends--------------- i_batch: 20.0 the loss is: 0.12680122 time for this batch: 0.597 -----------------a batch ends--------------- i_batch: 30.0 the loss is: 0.13160048 time for this batch: 0.577 -----------------a batch ends--------------- i_batch: 40.0 the loss is: 0.12789601 time for this batch: 0.611 -----------------a batch ends--------------- i_batch: 50.0 the loss is: 0.14020683 time for this batch: 0.565 -----------------a batch ends--------------- i_batch: 60.0 the loss is: 0.14430381 time for this batch: 0.555 -----------------a batch ends--------------- train loss for this epoch: 0.130875
----------------validate------------------- ave Recall 0.6688539605363211 ave NDCG 0.5634072626542452 ----------------test------------------- ave Recall 0.6578130977493277 ave NDCG 0.5494968553245554
running time for this epoch: 40.02163624763489 running time until now: 3639.215935230255 -------------------------an epoch ends --------------------------- i_epoch: 75 ----------------an epoch starts------------------- # batch: 63 i_batch: 0.0 the loss is: 0.12069584 time for this batch: 0.543 -----------------a batch ends--------------- i_batch: 10.0 the loss is: 0.12406084 time for this batch: 0.591 -----------------a batch ends--------------- i_batch: 20.0 the loss is: 0.13533404 time for this batch: 0.637 -----------------a batch ends--------------- i_batch: 30.0 the loss is: 0.14386395 time for this batch: 0.619 -----------------a batch ends--------------- i_batch: 40.0 the loss is: 0.12966727 time for this batch: 0.599 -----------------a batch ends--------------- i_batch: 50.0 the loss is: 0.12911506 time for this batch: 0.603 -----------------a batch ends--------------- i_batch: 60.0 the loss is: 0.12791108 time for this batch: 0.63 -----------------a batch ends--------------- train loss for this epoch: 0.131831
----------------validate------------------- ave Recall 0.6713738215485605 ave NDCG 0.5655989365042033 ----------------test------------------- ave Recall 0.6606173288376685 ave NDCG 0.5507045790871418
running time for this epoch: 41.45550799369812 running time until now: 3680.6715500354767 -------------------------an epoch ends --------------------------- i_epoch: 76 ----------------an epoch starts------------------- # batch: 63 i_batch: 0.0 the loss is: 0.13094473 time for this batch: 0.56 -----------------a batch ends--------------- i_batch: 10.0 the loss is: 0.14464201 time for this batch: 0.603 -----------------a batch ends--------------- i_batch: 20.0 the loss is: 0.12805495 time for this batch: 0.585 -----------------a batch ends--------------- i_batch: 30.0 the loss is: 0.14310677 time for this batch: 0.619 -----------------a batch ends--------------- i_batch: 40.0 the loss is: 0.13428456 time for this batch: 0.619 -----------------a batch ends--------------- i_batch: 50.0 the loss is: 0.12750609 time for this batch: 0.642 -----------------a batch ends--------------- i_batch: 60.0 the loss is: 0.12812465 time for this batch: 0.617 -----------------a batch ends--------------- train loss for this epoch: 0.131192
----------------validate------------------- ave Recall 0.665316383837415 ave NDCG 0.5596052875331353 ----------------test------------------- ave Recall 0.6576609494682308 ave NDCG 0.5472056136712383
running time for this epoch: 41.855536460876465 running time until now: 3722.5271587371826 -------------------------an epoch ends --------------------------- i_epoch: 77 ----------------an epoch starts------------------- # batch: 63 i_batch: 0.0 the loss is: 0.12909319 time for this batch: 0.59 -----------------a batch ends--------------- i_batch: 10.0 the loss is: 0.13042282 time for this batch: 0.614 -----------------a batch ends--------------- i_batch: 20.0 the loss is: 0.13863851 time for this batch: 0.654 -----------------a batch ends--------------- i_batch: 30.0 the loss is: 0.13575459 time for this batch: 0.624 -----------------a batch ends--------------- i_batch: 40.0 the loss is: 0.1255269 time for this batch: 0.611 -----------------a batch ends--------------- i_batch: 50.0 the loss is: 0.13040552 time for this batch: 0.606 -----------------a batch ends--------------- i_batch: 60.0 the loss is: 0.12913042 time for this batch: 0.6 -----------------a batch ends--------------- train loss for this epoch: 0.130283
----------------validate------------------- ave Recall 0.6707356773276891 ave NDCG 0.5656548118868017 ----------------test------------------- ave Recall 0.6603771851494664 ave NDCG 0.5502643743814501
running time for this epoch: 42.64535999298096 running time until now: 3765.1726081371307 -------------------------an epoch ends --------------------------- i_epoch: 78 ----------------an epoch starts------------------- # batch: 63 i_batch: 0.0 the loss is: 0.121602595 time for this batch: 0.565 -----------------a batch ends--------------- i_batch: 10.0 the loss is: 0.13362285 time for this batch: 0.631 -----------------a batch ends--------------- i_batch: 20.0 the loss is: 0.12596416 time for this batch: 0.638 -----------------a batch ends--------------- i_batch: 30.0 the loss is: 0.14215392 time for this batch: 0.661 -----------------a batch ends--------------- i_batch: 40.0 the loss is: 0.13873821 time for this batch: 0.609 -----------------a batch ends--------------- i_batch: 50.0 the loss is: 0.13979295 time for this batch: 0.631 -----------------a batch ends--------------- i_batch: 60.0 the loss is: 0.13355178 time for this batch: 0.596 -----------------a batch ends--------------- train loss for this epoch: 0.130976
----------------validate------------------- ave Recall 0.6709021994456124 ave NDCG 0.5655290759745827 ----------------test------------------- ave Recall 0.6592201768640102 ave NDCG 0.5494757959404108
running time for this epoch: 43.02607870101929 running time until now: 3808.198818206787 -------------------------an epoch ends --------------------------- i_epoch: 79 ----------------an epoch starts------------------- # batch: 63 i_batch: 0.0 the loss is: 0.11878429 time for this batch: 0.587 -----------------a batch ends--------------- i_batch: 10.0 the loss is: 0.12654349 time for this batch: 0.605 -----------------a batch ends--------------- i_batch: 20.0 the loss is: 0.12288368 time for this batch: 0.627 -----------------a batch ends--------------- i_batch: 30.0 the loss is: 0.1575127 time for this batch: 0.647 -----------------a batch ends--------------- i_batch: 40.0 the loss is: 0.13012607 time for this batch: 0.619 -----------------a batch ends--------------- i_batch: 50.0 the loss is: 0.13729611 time for this batch: 0.664 -----------------a batch ends--------------- i_batch: 60.0 the loss is: 0.13969326 time for this batch: 0.605 -----------------a batch ends--------------- train loss for this epoch: 0.130363
----------------validate------------------- ave Recall 0.6698384595592916 ave NDCG 0.5679479921880661 ----------------test------------------- ave Recall 0.6626746743158325 ave NDCG 0.5530482845958751
running time for this epoch: 42.773990869522095 running time until now: 3850.972934961319 -------------------------an epoch ends --------------------------- i_epoch: 80 ----------------an epoch starts------------------- # batch: 63 i_batch: 0.0 the loss is: 0.12779588 time for this batch: 0.56 -----------------a batch ends--------------- i_batch: 10.0 the loss is: 0.12304806 time for this batch: 0.522 -----------------a batch ends--------------- i_batch: 20.0 the loss is: 0.1263234 time for this batch: 0.622 -----------------a batch ends--------------- i_batch: 30.0 the loss is: 0.12860529 time for this batch: 0.606 -----------------a batch ends--------------- i_batch: 40.0 the loss is: 0.1266026 time for this batch: 0.614 -----------------a batch ends--------------- i_batch: 50.0 the loss is: 0.14162478 time for this batch: 0.617 -----------------a batch ends--------------- i_batch: 60.0 the loss is: 0.12781152 time for this batch: 0.609 -----------------a batch ends--------------- train loss for this epoch: 0.130753
----------------validate------------------- ave Recall 0.6672120814394598 ave NDCG 0.5640620238526131 ----------------test------------------- ave Recall 0.6591763717669132 ave NDCG 0.5524001178510207
Early stop at the 81-th epoch
print ("start preparing for vali and test")
vali_u_v, vali_x_poi, vali_x_user, vali_x_adj, vali_y_real = prepare_validate_test(vali, hyper_param)
test_u_v, test_x_poi, test_x_user, test_x_adj, test_y_real = prepare_validate_test(test, hyper_param)
start preparing for vali and test
#8.4: validate and test the model
print ("---------------validation-------------------")
all_recall, all_ndcg, ave_recall, ave_ndcg, vali_output, vali_real =\
validate_test(trained_model, hyper_param, vali_u_v, vali_x_poi, vali_x_user, vali_x_adj, vali_y_real, True)
print ("-----------finish model validation---------------")
---------------validation------------------- ave Recall 0.6672120814394598 ave NDCG 0.5640620238526131 -----------finish model validation---------------
print ("---------------test-------------------")
all_recall, all_ndcg, ave_recall, ave_ndcg, test_output, test_real =\
validate_test(trained_model, hyper_param, test_u_v, test_x_poi, test_x_user, test_x_adj, test_y_real, True)
print ("-----------finish model validation---------------")
---------------test------------------- ave Recall 0.6591763717669132 ave NDCG 0.5524001178510207 -----------finish model validation---------------
list_vali_hat = vali_output.cpu().detach().numpy().tolist()
list_vali_real = vali_real.cpu().detach().numpy().tolist()
print(len(list_vali_hat))
print(len(list_vali_hat[0]))
print(len(list_vali_hat[0][0]))
print(len(list_vali_hat[0][0][0]))
list_test_hat = test_output.cpu().detach().numpy().tolist()
list_test_real = test_real.cpu().detach().numpy().tolist()
print(len(list_test_hat))
print(len(list_test_hat[0]))
print(len(list_test_hat[0][0]))
print(len(list_test_hat[0][0][0]))
18 1 1827 80 36 1 1827 80
result = {"vali_hat": list_vali_hat, "vali_real": list_vali_real, \
"test_hat": list_test_hat, "test_real": list_test_real}
subfile = case+'/vali_predict.json'
savefile = open(subfile,'w')
json.dump(result, savefile)
savefile.close()
df = json.load(open(subfile))
df.keys()
print(len(df["test_real"]))
36